scholarly journals A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex

Nature ◽  
2021 ◽  
Vol 598 (7879) ◽  
pp. 103-110 ◽  
Author(s):  
Zizhen Yao ◽  
Hanqing Liu ◽  
Fangming Xie ◽  
Stephan Fischer ◽  
Ricky S. Adkins ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Neuronal Cell ◽  
Pyramidal Cells ◽  
Cell Types ◽  
Regulatory Elements ◽  
Marker Genes ◽  
Specific Cell ◽  
Cell Type ◽  
The Brain

AbstractSingle-cell transcriptomics can provide quantitative molecular signatures for large, unbiased samples of the diverse cell types in the brain1–3. With the proliferation of multi-omics datasets, a major challenge is to validate and integrate results into a biological understanding of cell-type organization. Here we generated transcriptomes and epigenomes from more than 500,000 individual cells in the mouse primary motor cortex, a structure that has an evolutionarily conserved role in locomotion. We developed computational and statistical methods to integrate multimodal data and quantitatively validate cell-type reproducibility. The resulting reference atlas—containing over 56 neuronal cell types that are highly replicable across analysis methods, sequencing technologies and modalities—is a comprehensive molecular and genomic account of the diverse neuronal and non-neuronal cell types in the mouse primary motor cortex. The atlas includes a population of excitatory neurons that resemble pyramidal cells in layer 4 in other cortical regions4. We further discovered thousands of concordant marker genes and gene regulatory elements for these cell types. Our results highlight the complex molecular regulation of cell types in the brain and will directly enable the design of reagents to target specific cell types in the mouse primary motor cortex for functional analysis.

scholarly journals Comparative cellular analysis of motor cortex in human, marmoset and mouse

Nature ◽  
2021 ◽  
Vol 598 (7879) ◽  
pp. 111-119 ◽  
Author(s):  
Trygve E. Bakken ◽  
Nikolas L. Jorstad ◽  
Qiwen Hu ◽  
Blue B. Lake ◽  
Wei Tian ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Neuronal Cell ◽  
Cell Types ◽  
Morphological Characterization ◽  
Fine Motor ◽  
Marker Genes ◽  
Cell Type ◽  
Regulatory Pathways ◽  
Cellular Analysis

AbstractThe primary motor cortex (M1) is essential for voluntary fine-motor control and is functionally conserved across mammals1. Here, using high-throughput transcriptomic and epigenomic profiling of more than 450,000 single nuclei in humans, marmoset monkeys and mice, we demonstrate a broadly conserved cellular makeup of this region, with similarities that mirror evolutionary distance and are consistent between the transcriptome and epigenome. The core conserved molecular identities of neuronal and non-neuronal cell types allow us to generate a cross-species consensus classification of cell types, and to infer conserved properties of cell types across species. Despite the overall conservation, however, many species-dependent specializations are apparent, including differences in cell-type proportions, gene expression, DNA methylation and chromatin state. Few cell-type marker genes are conserved across species, revealing a short list of candidate genes and regulatory mechanisms that are responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allows us to use patch–seq (a combination of whole-cell patch-clamp recordings, RNA sequencing and morphological characterization) to identify corticospinal Betz cells from layer 5 in non-human primates and humans, and to characterize their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell-type diversity in M1 across mammals, and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

scholarly journals Deciphering how specialized interneuron-specific cell types contribute to circuit function

2020 ◽  
Author(s):  
Alexandre Guet-McCreight ◽  
Frances K Skinner
Keyword(s):  
Computational Models ◽  
Brain Area ◽  
Pyramidal Cells ◽  
Cell Types ◽  
Specific Cell ◽  
Cell Type ◽  
Inhibitory Cell ◽  
Cell Firing ◽  
The Brain

AbstractThe wide diversity of inhibitory cells across the brain makes them fit to contribute to network dynamics in specialized fashions. However, the contributions of a particular inhibitory cell type in a behaving animal is challenging to decipher as one needs to both record cellular activities and identify the cell type being recorded. Thus, using computational modeling to explore cell-specific contributions so as to predict and hypothesize functional contributions is desirable. Here we examine potential contributions of interneuron-specific 3 (I-S3) cells - a type of inhibitory interneuron found in CA1 hippocampus that only targets other inhibitory interneurons - during simulated theta rhythms. We use previously developed multi-compartment models of oriens lacunosum-moleculare (OLM) cells, the main target of I-S3 cells, and explore how I-S3 cell inputs during in vitro and in vivo scenarios contribute to theta. We find that I-S3 cells suppress OLM cell spiking, rather than engender its spiking via post-inhibitory rebound mechanisms. To elicit recruitment similar to experiment, the inclusion of disinhibited pyramidal cell inputs is necessary, suggesting that I-S3 cell firing can broaden the window for disinhibiting pyramidal cells. Using in vivo virtual networks, we show that I-S3 cells can contribute to a sharpening of OLM cell recruitment at theta frequencies. Further, a shifting of the timing of I-S3 cell spiking due to external modulation can shift the timing of the OLM cell firing and thus disinhibitory windows. We thus propose a specialized contribution of I-S3 cells to create temporally precise coordination of modulation pathways.Significance StatementHow information is processed across different brain structures is an important question that relates to the different functions that the brain performs. In this work we use computational models that focus on a particular inhibitory cell type that only inhibits other inhibitory cell types – the I-S3 cell in the hippocampus. We show that this cell type is able to broaden the window for disinhibition of excitatory cells. We further illustrate that this broadening presents itself as a mechanism for input pathway switching and modulation over the timing of inhibitory cell spiking. Overall, this work contributes to our knowledge of how coordination between sensory and memory consolidation information is attained in a brain area that is involved in memory formation.

scholarly journals An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types

2020 ◽  
Author(s):  
Zizhen Yao ◽  
Hanqing Liu ◽  
Fangming Xie ◽  
Stephan Fischer ◽  
A. Sina Booeshaghi ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Single Cell ◽  
Primary Motor Cortex ◽  
Neuronal Cell ◽  
Cell Types ◽  
Regulatory Elements ◽  
Brain Cell ◽  
Molecular Signatures ◽  
Sequencing Technologies ◽  
Cell Transcriptome

AbstractSingle cell transcriptomics has transformed the characterization of brain cell identity by providing quantitative molecular signatures for large, unbiased samples of brain cell populations. With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp. Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis.

scholarly journals Multiscale Co-Expression in the Brain

2020 ◽  
Author(s):  
Benjamin D. Harris ◽  
Megan Crow ◽  
Stephan Fischer ◽  
Jesse Gillis
Keyword(s):  
Motor Cortex ◽  
Single Cell ◽  
Rna Sequencing ◽  
Primary Motor Cortex ◽  
Cell Types ◽  
Cell Type ◽  
Single Cell Rna Sequencing ◽  
Cell Type Specific ◽  
The Brain ◽  
Regulatory Landscape

ABSTRACTSingle-cell RNA-sequencing (scRNAseq) data can reveal co-regulatory relationships between genes that may be hidden in bulk RNAseq due to cell type confounding. Using the primary motor cortex data from the Brain Initiative Cell Census Network (BICCN), we study cell type specific co-expression across 500,000 cells. Surprisingly, we find that the same gene-gene relationships that differentiate cell types are evident at finer and broader scales, suggesting a consistent multiscale regulatory landscape.

scholarly journals Brain Data Standards Ontology: A data-driven ontology of transcriptomically defined cell types in the primary motor cortex

2021 ◽  
Author(s):  
Shawn Zheng Kai Tan ◽  
Huseyin Kir ◽  
Brian Aevermann ◽  
Tom Gillespie ◽  
Michael Hawrylycz ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Single Cell ◽  
Primary Motor Cortex ◽  
Cell Types ◽  
Use Cases ◽  
Data Driven ◽  
Cell Type ◽  
Data Standards ◽  
Brain Data ◽  
The Brain

Large scale single cell omics profiling is revolutionising our understanding of cell types, especially in complex organs like the brain. This presents both an opportunity and a challenge for cell ontologies. Annotation of cell types in single cell 'omics data typically uses unstructured free text, making comparison and mapping of annotation between datasets challenging. Annotation with cell ontologies is key to overcoming this challenge, but this will require meeting the challenge of extending cell ontologies representing classically defined cell types by defining and classifying cell types directly from data. Here we present the Brain Data Standards Ontology (BDSO), a data driven ontology that is built as an extension to the Cell Ontology (CL). It supports two major use cases: cell type annotation, and navigation, search, and organisation of a web application integrating single cell omics datasets for the mammalian primary motor cortex. The ontology is built using a semi-automated pipeline that interlinks cell type taxonomies and necessary and sufficient marker genes, and imports relevant ontology modules derived from external ontologies. Overall, the BDS ontology provides an underlying structure that supports these use cases, while remaining sustainable and extensible through automation as our knowledge of brain cell type expands.

scholarly journals Cell-Type Specific Responses to Associative Learning in the Primary Motor Cortex

2021 ◽  
Author(s):  
Candice Lee ◽  
Emerson Harkin ◽  
Richard Naud ◽  
Simon Chen
Keyword(s):  
Motor Cortex ◽  
Associative Learning ◽  
Primary Motor Cortex ◽  
Neuronal Cell ◽  
Cell Types ◽  
Skill Learning ◽  
Cell Type ◽  
Movement Initiation ◽  
Response Properties ◽  
Cell Type Specific

The primary motor cortex (M1) is known to be a critical site for movement initiation and motor learning. Surprisingly, it has also been shown to possess reward-related activity, presumably to facilitate reward-based learning of new movements. However, whether reward-related signals are represented among different cell types in M1, and whether their response properties change after cue-reward conditioning remains unclear. Here, we performed longitudinal in vivo two-photon Ca2+ imaging to monitor the activity of different neuronal cell types in M1 while mice engaged in a classical conditioning task. Our results demonstrate that most of the major neuronal cell types in M1 showed robust but differential responses to both cue and reward stimuli, and their response properties undergo cell-type specific modifications after associative learning. PV-INs' responses became more reliable to the cue stimulus, while VIP-INs' responses became more reliable to the reward stimulus. PNs only showed robust response to the novel reward stimulus, and they habituated to it after associative learning. Lastly, SOM-IN responses emerged and became more reliable to both conditioned cue and reward stimuli after conditioning. These observations suggest that cue- and reward-related signals are represented among different neuronal cell types in M1, and the distinct modifications they undergo during associative learning could be essential in triggering different aspects of local circuit reorganization in M1 during reward-based motor skill learning.

scholarly journals Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse

2020 ◽  
Author(s):  
Trygve E. Bakken ◽  
Nikolas L. Jorstad ◽  
Qiwen Hu ◽  
Blue B. Lake ◽  
Wei Tian ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Primary Motor Cortex ◽  
Cell Types ◽  
Fine Motor ◽  
Marker Genes ◽  
Cell Type ◽  
Regulatory Pathways ◽  
Marmoset Monkey ◽  
Chandelier Cells ◽  
Species Specific

AbstractThe primary motor cortex (M1) is essential for voluntary fine motor control and is functionally conserved across mammals. Using high-throughput transcriptomic and epigenomic profiling of over 450,000 single nuclei in human, marmoset monkey, and mouse, we demonstrate a broadly conserved cellular makeup of this region, whose similarity mirrors evolutionary distance and is consistent between the transcriptome and epigenome. The core conserved molecular identity of neuronal and non-neuronal types allowed the generation of a cross-species consensus cell type classification and inference of conserved cell type properties across species. Despite overall conservation, many species specializations were apparent, including differences in cell type proportions, gene expression, DNA methylation, and chromatin state. Few cell type marker genes were conserved across species, providing a short list of candidate genes and regulatory mechanisms responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allowed the Patch-seq identification of layer 5 (L5) corticospinal Betz cells in non-human primate and human and characterization of their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell type diversity in M1 across mammals and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

scholarly journals SSMD: a semi-supervised approach for a robust cell type identification and deconvolution of mouse transcriptomics data

2020 ◽  
Author(s):  
Xiaoyu Lu ◽  
Szu-Wei Tu ◽  
Wennan Chang ◽  
Changlin Wan ◽  
Jiashi Wang ◽  
...  
Keyword(s):  
Small Sample Size ◽  
Cell Types ◽  
Small Sample ◽  
Training Data ◽  
Mouse Tissue ◽  
Marker Genes ◽  
Specific Cell ◽  
Cell Type ◽  
Data Set ◽  
Transcriptomics Data

Abstract Deconvolution of mouse transcriptomic data is challenged by the fact that mouse models carry various genetic and physiological perturbations, making it questionable to assume fixed cell types and cell type marker genes for different data set scenarios. We developed a Semi-Supervised Mouse data Deconvolution (SSMD) method to study the mouse tissue microenvironment. SSMD is featured by (i) a novel nonparametric method to discover data set-specific cell type signature genes; (ii) a community detection approach for fixing cell types and their marker genes; (iii) a constrained matrix decomposition method to solve cell type relative proportions that is robust to diverse experimental platforms. In summary, SSMD addressed several key challenges in the deconvolution of mouse tissue data, including: (i) varied cell types and marker genes caused by highly divergent genotypic and phenotypic conditions of mouse experiment; (ii) diverse experimental platforms of mouse transcriptomics data; (iii) small sample size and limited training data source and (iv) capable to estimate the proportion of 35 cell types in blood, inflammatory, central nervous or hematopoietic systems. In silico and experimental validation of SSMD demonstrated its high sensitivity and accuracy in identifying (sub) cell types and predicting cell proportions comparing with state-of-the-arts methods. A user-friendly R package and a web server of SSMD are released via https://github.com/xiaoyulu95/SSMD.

scholarly journals A multimodal cell census and atlas of the mammalian primary motor cortex

2020 ◽  
Author(s):  
◽  
Ricky S. Adkins ◽  
Andrew I. Aldridge ◽  
Shona Allen ◽  
Seth A. Ament ◽  
...  
Keyword(s):  
Motor Cortex ◽  
Single Cell ◽  
Primary Motor Cortex ◽  
Spatial Information ◽  
Molecular Genetic ◽  
Cell Types ◽  
Developmental Trajectory ◽  
Open Chromatin ◽  
Cell Type ◽  
Spatially Resolved

ABSTRACTWe report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex (MOp or M1) as the initial product of the BRAIN Initiative Cell Census Network (BICCN). This was achieved by coordinated large-scale analyses of single-cell transcriptomes, chromatin accessibility, DNA methylomes, spatially resolved single-cell transcriptomes, morphological and electrophysiological properties, and cellular resolution input-output mapping, integrated through cross-modal computational analysis. Together, our results advance the collective knowledge and understanding of brain cell type organization: First, our study reveals a unified molecular genetic landscape of cortical cell types that congruently integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a unified taxonomy of transcriptomic types and their hierarchical organization that are conserved from mouse to marmoset and human. Third, cross-modal analysis provides compelling evidence for the epigenomic, transcriptomic, and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types and subtypes. Fourth, in situ single-cell transcriptomics provides a spatially-resolved cell type atlas of the motor cortex. Fifth, integrated transcriptomic, epigenomic and anatomical analyses reveal the correspondence between neural circuits and transcriptomic cell types. We further present an extensive genetic toolset for targeting and fate mapping glutamatergic projection neuron types toward linking their developmental trajectory to their circuit function. Together, our results establish a unified and mechanistic framework of neuronal cell type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

scholarly journals Inference of cell-type specific imprinted regulatory elements and genes during human neuronal differentiation

2021 ◽  
Author(s):  
Dan Liang ◽  
Nil Aygün ◽  
Nana Matoba ◽  
Folami Ideraabdullah ◽  
Michael I Love ◽  
...  
Keyword(s):  
Gene Expression ◽  
Neural Progenitor Cells ◽  
Association Studies ◽  
Cpg Islands ◽  
Uniparental Disomy ◽  
Cell Types ◽  
Regulatory Elements ◽  
Imprinted Genes ◽  
Specific Cell ◽  
Cell Type

Genomic imprinting results in gene expression biased by parental chromosome of origin and occurs in genes with important roles during human brain development. However, the cell-type and temporal specificity of imprinting during human neurogenesis is generally unknown. By detecting within-donor allelic biases in chromatin accessibility and gene expression that are unrelated to cross-donor genotype, we inferred imprinting in both primary human neural progenitor cells (phNPCs) and their differentiated neuronal progeny from up to 85 donors. We identified 43/20 putatively imprinted regulatory elements (IREs) in neurons/progenitors, and 133/79 putatively imprinted genes in neurons/progenitors. Though 10 IREs and 42 genes were shared between neurons and progenitors, most imprinting was only detected within specific cell types. In addition to well-known imprinted genes and their promoters, we inferred novel IREs and imprinted genes. We found IREs overlapped with CpG islands more than non-imprinted regulatory elements. Consistent with DNA methylation-based regulation of imprinted expression, some putatively imprinted regulatory elements also overlapped with differentially methylated regions on the maternal germline. Finally, we identified a progenitor-specific putatively imprinted gene overlap with copy number variation that is associated with uniparental disomy-like phenotypes. Our results can therefore be useful in interpreting the function of variants identified in future parent-of-origin association studies.

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