scholarly journals Connectivity characterization of the mouse basolateral amygdalar complex

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Houri Hintiryan ◽  
Ian Bowman ◽  
David L. Johnson ◽  
Laura Korobkova ◽  
Muye Zhu ◽  
...  
Keyword(s):  
Granular Cell ◽  
Cell Types ◽  
Projection Neurons ◽  
Cell Type ◽  
Connectivity Map ◽  
Analysis Techniques ◽  
Domain Specific ◽  
Cell Type Specific ◽  
Unique Domain

AbstractThe basolateral amygdalar complex (BLA) is implicated in behaviors ranging from fear acquisition to addiction. Optogenetic methods have enabled the association of circuit-specific functions to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. Here, we apply machine-learning based computational and informatics analysis techniques to the results of circuit-tracing experiments to create a foundational, comprehensive BLA connectivity map. The analyses identify three distinct domains within the anterior BLA (BLAa) that house target-specific projection neurons with distinguishable morphological features. We identify brain-wide targets of projection neurons in the three BLAa domains, as well as in the posterior BLA, ventral BLA, posterior basomedial, and lateral amygdalar nuclei. Inputs to each nucleus also are identified via retrograde tracing. The data suggests that connectionally unique, domain-specific BLAa neurons are associated with distinct behavior networks.

scholarly journals Connectivity characterization of the mouse basolateral amygdalar complex

2019 ◽  
Author(s):  
Houri Hintiryan ◽  
Ian Bowman ◽  
David L. Johnson ◽  
Laura Korobkova ◽  
Muye Zhu ◽  
...  
Keyword(s):  
Cell Body ◽  
Computational Analysis ◽  
Functional Characterization ◽  
Granular Cell ◽  
Cell Types ◽  
Projection Neurons ◽  
Cell Type ◽  
Analysis Techniques ◽  
Cell Type Specific

ABSTRACTThe basolateral amygdalar complex (BLA) is implicated in behavioral processing ranging from fear acquisition to addiction. Newer methods like optogenetics have enabled the association of circuit-specific functionality to uniquely connected BLA cell types. Thus, a systematic and detailed connectivity profile of BLA projection neurons to inform granular, cell type-specific interrogations is warranted. In this work, we applied computational analysis techniques to the results of our circuit-tracing experiments to create a foundational, comprehensive, multiscale connectivity atlas of the mouse BLA. The analyses identified three domains within the classically defined anterior BLA (BLAa) that house target-specific projection neurons with distinguishable cell body and dendritic morphologies. Further, we identify brain-wide targets of projection neurons located in the three BLAa domains as well as in the posterior BLA (BLAp), ventral BLA (BLAv), lateral (LA), and posterior basomedial (BMAp) nuclei. Projection neurons that provide input to each nucleus are also identifed. Functional characterization of some projection-defined BLA neurons were demonstrated via optogenetic and recording experiments. Hypotheses relating function to connection-defined BLA cell types are proposed.

scholarly journals Bulk Tissue Cell Type Deconvolution with Multi-Subject Single-Cell Expression Reference

2018 ◽  
Author(s):  
Xuran Wang ◽  
Jihwan Park ◽  
Katalin Susztak ◽  
Nancy R. Zhang ◽  
Mingyao Li
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Cellular Heterogeneity ◽  
Tissue Cell ◽  
Specific Gene ◽  
Rna Seq ◽  
Cell Type ◽  
Cell Type Specific ◽  
Cell Expression

AbstractWe present MuSiC, a method that utilizes cell-type specific gene expression from single-cell RNA sequencing (RNA-seq) data to characterize cell type compositions from bulk RNA-seq data in complex tissues. When applied to pancreatic islet and whole kidney expression data in human, mouse, and rats, MuSiC outperformed existing methods, especially for tissues with closely related cell types. MuSiC enables characterization of cellular heterogeneity of complex tissues for identification of disease mechanisms.

scholarly journals Subcellular sequencing of single neurons reveals the dendritic transcriptome of GABAergic interneurons

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Julio D Perez ◽  
Susanne tom Dieck ◽  
Beatriz Alvarez-Castelao ◽  
Georgi Tushev ◽  
Ivy CW Chan ◽  
...  
Keyword(s):  
Hippocampal Neurons ◽  
Large Population ◽  
Cell Types ◽  
Mrna Localization ◽  
Gabaergic Neurons ◽  
Local Translation ◽  
Single Neurons ◽  
Cell Type ◽  
Cell Type Specific

Although mRNAs are localized in the processes of excitatory neurons, it is still unclear whether interneurons also localize a large population of mRNAs. In addition, the variability in the localized mRNA population within and between cell-types is unknown. Here we describe the unbiased transcriptomic characterization of the subcellular compartments of hundreds of single neurons. We separately profiled the dendritic and somatic transcriptomes of individual rat hippocampal neurons and investigated mRNA abundances in the soma and dendrites of single glutamatergic and GABAergic neurons. We found that, like their excitatory counterparts, interneurons contain a rich repertoire of ~4000 mRNAs. We observed more cell type-specific features among somatic transcriptomes than their associated dendritic transcriptomes. Finally, using cell-type specific metabolic labelling of isolated neurites, we demonstrated that the processes of Glutamatergic and, notably, GABAergic neurons were capable of local translation, suggesting mRNA localization and local translation is a general property of neurons.

scholarly journals Cell type-specific membrane potential changes in dorsolateral striatum accompanying reward-based sensorimotor learning

Function ◽  
2021 ◽  
Author(s):  
Tanya Sippy ◽  
Corryn Chaimowitz ◽  
Sylvain Crochet ◽  
Carl C H Petersen
Keyword(s):  
Membrane Potential ◽  
Dopamine Receptors ◽  
Cell Types ◽  
Projection Neurons ◽  
Striatal Neurons ◽  
Cell Type ◽  
Indirect Pathway ◽  
Cell Type Specific ◽  
Striatal Membrane ◽  
Sensory Evoked

Abstract The striatum integrates sensorimotor and motivational signals, likely playing a key role in reward-based learning of goal-directed behavior. However, cell type-specific mechanisms underlying reinforcement learning remain to be precisely determined. Here, we investigated changes in membrane potential dynamics of dorsolateral striatal neurons comparing naïve mice and expert mice trained to lick a reward spout in response to whisker deflection. We recorded from three distinct cell types: i) direct pathway striatonigral neurons, which express type 1 dopamine receptors; ii) indirect pathway striatopallidal neurons, which express type 2 dopamine receptors; and iii) tonically active, putative cholinergic, striatal neurons. Task learning was accompanied by cell type-specific changes in the membrane potential dynamics evoked by the whisker deflection and licking in successfully-performed trials. Both striatonigral and striatopallidal types of striatal projection neurons showed enhanced task-related depolarization across learning. Striatonigral neurons showed a prominent increase in a short latency sensory-evoked depolarization in expert compared to naïve mice. In contrast, the putative cholinergic striatal neurons developed a hyperpolarizing response across learning, driving a pause in their firing. Our results reveal cell type-specific changes in striatal membrane potential dynamics across the learning of a simple goal-directed sensorimotor transformation, helpful for furthering the understanding of the various potential roles of different basal ganglia circuits.

scholarly journals Joint inference and alignment of genome structures enables characterization of compartment-independent reorganization across cell types

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Lila Rieber ◽  
Shaun Mahony
Keyword(s):  
K562 Cells ◽  
Cell Types ◽  
Data Sets ◽  
Cell Type ◽  
Histone Marks ◽  
Joint Inference ◽  
3D Localization ◽  
Topologically Associated Domains ◽  
Cell Type Specific

Abstract Background Comparisons of Hi–C data sets between cell types and conditions have revealed differences in topologically associated domains (TADs) and A/B compartmentalization, which are correlated with differences in gene regulation. However, previous comparisons have focused on known forms of 3D organization while potentially neglecting other functionally relevant differences. We aimed to create a method to quantify all locus-specific differences between two Hi–C data sets. Results We developed MultiMDS to jointly infer and align 3D chromosomal structures from two Hi–C data sets, thereby enabling a new way to comprehensively quantify relocalization of genomic loci between cell types. We demonstrate this approach by comparing Hi–C data across a variety of cell types. We consistently find relocalization of loci with minimal difference in A/B compartment score. For example, we identify compartment-independent relocalizations between GM12878 and K562 cells that involve loci displaying enhancer-associated histone marks in one cell type and polycomb-associated histone marks in the other. Conclusions MultiMDS is the first tool to identify all loci that relocalize between two Hi–C data sets. Our method can identify 3D localization differences that are correlated with cell-type-specific regulatory activities and which cannot be identified using other methods.

scholarly journals Transcriptome analysis for the development of cell-type specific labeling to study olfactory circuits

2020 ◽  
Author(s):  
Anzhelika Koldaeva ◽  
Cary Zhang ◽  
Yu-Pei Huang ◽  
Janine Reinert ◽  
Seiya Mizuno ◽  
...  
Keyword(s):  
Transcriptome Analysis ◽  
Mrna Level ◽  
Sensory System ◽  
Cell Types ◽  
Projection Neurons ◽  
Dependent Manner ◽  
Cell Type ◽  
Cell Type Specific ◽  
Sensory Evoked ◽  
Driver Line

AbstractIn each sensory system of the brain, mechanisms exist to extract distinct features from stimuli to generate a variety of behavioural repertoires. These often correspond to different cell types at some stage in sensory processing. In the mammalian olfactory system, complex information processing starts in the olfactory bulb, whose output is conveyed by mitral and tufted cells (MCs and TCs). Despite many differences between them, and despite the crucial position they occupy in the information hierarchy, little is known how these two types of projection neurons differ at the mRNA level. Here, we sought to identify genes that are differentially expressed between MCs and TCs, with an ultimate goal to generate a cell-type specific Cre-driver line, starting from a transcriptome analysis using a large and publicly available single-cell RNA-seq dataset (Zeisel et al., 2018). Despite many genes showing differential expressions, we identified only a few that were abundantly and consistently expressed only in MCs. After further validating these putative markers using in-situ hybridization, two genes, namely Pkib and Lbdh2, remained as promising candidates. Using CRISPR/Cas9-mediated gene editing, we generated Cre-driver lines and analysed the resulting recombination patterns. This analysis indicated that our new inducible Cre-driver line, Lbhd2-CreERT2, can be used to genetically label MCs in a tamoxifen dose-dependent manner, as assessed by soma locations, projection patterns and sensory-evoked responses. Hence this line is a promising tool for future investigations of cell-type specific contributions to olfactory processing and demonstrates the power of publicly accessible data in accelerating science.

scholarly journals Single-cell analysis of Foxp1-driven mechanisms essential for striatal development

2019 ◽  
Author(s):  
Ashley G. Anderson ◽  
Ashwinikumar Kulkarni ◽  
Matthew Harper ◽  
Genevieve Konopka
Keyword(s):  
Single Cell ◽  
Target Genes ◽  
Single Cell Analysis ◽  
Cell Types ◽  
Brain Regions ◽  
Projection Neurons ◽  
Loss Of Function ◽  
Cell Type ◽  
Motor Information ◽  
Cell Type Specific

AbstractThe striatum is a critical forebrain structure for integrating cognitive, sensory, and motor information from diverse brain regions into meaningful behavioral output. However, the transcriptional mechanisms that underlie striatal development and organization at single-cell resolution remain unknown. Here, we show that Foxp1, a transcription factor strongly linked to autism and intellectual disability, regulates organizational features of striatal circuitry in a cell-type-dependent fashion. Using single-cell RNA-sequencing, we examine the cellular diversity of the early postnatal striatum and find that cell-type-specific deletion ofFoxp1in striatal projection neurons alters the cellular composition and neurochemical architecture of the striatum. Importantly, using this approach, we identify the non-cell autonomous effects produced by disruptingFoxp1in one cell-type and the molecular compensation that occurs in other populations. Finally, we identify Foxp1-regulated target genes within distinct cell-types and connect these molecular changes to functional and behavioral deficits relevant to phenotypes described in patients withFOXP1loss-of-function mutations. These data reveal cell-type-specific transcriptional mechanisms underlying distinct features of striatal circuitry and identify Foxp1 as a key regulator of striatal development.

scholarly journals Subcellular sequencing of single neurons reveals the dendritic transcriptome of GABAergic interneurons

2020 ◽  
Author(s):  
Julio D. Perez ◽  
Susanne tom Dieck ◽  
Beatriz Alvarez-Castelao ◽  
Ivy C.W. Chan ◽  
Erin M. Schuman
Keyword(s):  
Hippocampal Neurons ◽  
Large Population ◽  
Cell Types ◽  
Gabaergic Neurons ◽  
Gabaergic Interneurons ◽  
Local Translation ◽  
Cell Type ◽  
Cell Type Specific ◽  
The Individual

AbstractThe localization and translation of mRNAs to dendrites and axons maintains and modifies the local proteome of neurons, and is essential for synaptic plasticity. Although significant efforts have allowed the identification of localized mRNAs in excitatory neurons, it is still unclear whether interneurons also localize a large population of mRNAs. In addition, the variability in the population of localized mRNAs within and between cell-types is unknown. Here we developed a method for the transcriptomic characterization of a single neuron’s subcellular compartments, which combines laser capture microdissection with scRNA-seq. This allowed us to separately profile the dendritic and somatic transcriptomes of individual rat hippocampal neurons and investigate the relation in mRNA abundances between the soma and dendrites of single glutamatergic and GABAergic neurons. We identified two types of glutamatergic and three types of GABAergic interneurons and we found that, like their excitatory counterparts, interneurons contain a rich repertoire of ~4000 mRNAs. The individual somatic transcriptomes exhibited more cell type-specific features than their associated dendritic transcriptomes. The detection and abundance of dendritic mRNAs was not always simply predicted by their somatic counterparts. Finally, using cell-type specific metabolic labelling of isolated neurites, we demonstrated that the processes not only of Glutamatergic but also of GABAergic neurons are capable of local translation, suggesting mRNA localization and local translation is a general property of neurons.

scholarly journals Gap Junctions Between Striatal D1 Neurons and Cholinergic Interneurons

2021 ◽  
Vol 15 ◽  
Author(s):  
Yuqi Ren ◽  
Yang Liu ◽  
Minmin Luo
Keyword(s):  
Gap Junctions ◽  
Electrical Coupling ◽  
Cell Types ◽  
Projection Neurons ◽  
Chemical Synapse ◽  
Cell Type ◽  
Cholinergic Interneurons ◽  
Optogenetic Stimulation ◽  
Electrophysiological Recordings ◽  
Cell Type Specific

The striatum participates in numerous important behaviors. Its principal projection neurons use GABA and peptides as neurotransmitters and interact extensively with interneurons, including cholinergic interneurons (ChIs) that are tonically active. Dissecting the interactions between projection neurons and ChIs is important for uncovering the role and mechanisms of the striatal microcircuits. Here, by combining several optogenetic tools with cell type-specific electrophysiological recordings, we uncovered direct electrical coupling between D1-type projection neurons and ChIs, in addition to the chemical transmission between these two major cell types. Optogenetic stimulation or inhibition led to bilateral current exchanges between D1 neurons and ChIs, which can be abolished by gap junction blockers. We further confirmed the presence of gap junctions through paired electrophysiological recordings and dye microinjections. Finally, we found that activating D1 neurons promotes basal activity of ChIs via gap junctions. Collectively, these results reveal the coexistence of the chemical synapse and gap junctions between D1 neurons and ChIs, which contributes to maintaining the tonically active firing patterns of ChIs.

scholarly journals Reproducibility and reusability limitations in Regulatory Circuits: analysis and solutions

2021 ◽  
Author(s):  
Marine Louarn ◽  
Anne Siegel ◽  
Thierry Fest ◽  
Olivier Dameron ◽  
Fabrice Chatonnet
Keyword(s):  
Data Integration ◽  
Regulatory Networks ◽  
Cell Types ◽  
Biological Data ◽  
Google Scholar ◽  
Cell Type ◽  
Regulatory Circuits ◽  
Cell Type Specific ◽  
Different Levels

The Regulatory Circuits project is among the most recent and the most complete attempts to identify cell-type specific regulatory networks in Human. It is one of the largest efforts of public genomics data integration, based on data from the major consortia FANTOM5, ENCODE and Roadmap Epigenomics. This project is a main provider of biological data, cited more than 224 times (Google Scholar) and its resulting networks were used in at least 42 other articles. For such a general resource, reproducibility of both the outputs (regulation networks) and methods (data integration pipeline) is a major issue, since biological data are updated regularly. In addition, users may want to introduce new data into the Regulatory Circuits framework to provide networks about previously uncharacterized cell types or to add information about specific regulators, which require to re-execute the whole pipeline on the new data. In this article, we analyze the various factors limiting reproducibility of the Regulatory Circuits data and methods. Starting from a factual description of our understanding of the methods used in Regulatory Circuits, our contribution is two-fold: we propose (1) a characterization of the different levels of reusability, reproducibility and conceptual issues in the original workflow and (2) a new implementation of the workflow ensuring its consistency with the published description and allowing for an easier reuse and reproduction of the published outputs. Both are applicable beyond the case of Regulatory Circuits.

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