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

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.

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Multiscale Co-Expression in the Brain

10.1101/2020.03.31.018630 ◽

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.

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

10.1101/2020.10.19.343129 ◽

2020 ◽

Cited By ~ 5

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.

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

Nature ◽

10.1038/s41586-021-03500-8 ◽

2021 ◽

Vol 598 (7879) ◽

pp. 103-110 ◽

Cited By ~ 6

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.

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

Nature ◽

10.1038/s41586-021-03465-8 ◽

2021 ◽

Vol 598 (7879) ◽

pp. 111-119 ◽

Cited By ~ 1

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.

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Cell type-specific aging clocks to quantify aging and rejuvenation in regenerative regions of the brain

10.1101/2022.01.10.475747 ◽

2022 ◽

Author(s):

Matthew T Buckley ◽

Eric Sun ◽

Benson M. George ◽

Ling Liu ◽

Nicholas Schaum ◽

...

Keyword(s):

Single Cell ◽

Cell Types ◽

Rna Seq ◽

Cell Type ◽

Cell Level ◽

Transcriptomic Data ◽

Precise Quantification ◽

Cell Type Specific ◽

Tissue Aging ◽

The Brain

Aging manifests as progressive dysfunction culminating in death. The diversity of cell types is a challenge to the precise quantification of aging and its reversal. Here we develop a suite of 'aging clocks' based on single cell transcriptomic data to characterize cell type-specific aging and rejuvenation strategies. The subventricular zone (SVZ) neurogenic region contains many cell types and provides an excellent system to study cell-level tissue aging and regeneration. We generated 21,458 single-cell transcriptomes from the neurogenic regions of 28 mice, tiling ages from young to old. With these data, we trained a suite of single cell-based regression models (aging clocks) to predict both chronological age (passage of time) and biological age (fitness, in this case the proliferative capacity of the neurogenic region). Both types of clocks perform well on independent cohorts of mice. Genes underlying the single cell-based aging clocks are mostly cell-type specific, but also include a few shared genes in the interferon and lipid metabolism pathways. We used these single cell-based aging clocks to measure transcriptomic rejuvenation, by generating single cell RNA-seq datasets of SVZ neurogenic regions for two interventions - heterochronic parabiosis (young blood) and exercise. Interestingly, the use of aging clocks reveals that both heterochronic parabiosis and exercise reverse transcriptomic aging in the niche, but in different ways across cell types and genes. This study represents the first development of high-resolution aging clocks from single cell transcriptomic data and demonstrates their application to quantify transcriptomic rejuvenation.

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Single cell transcriptome profiling of the human alcohol-dependent brain

10.1101/780304 ◽

2019 ◽

Author(s):

Eric Brenner ◽

Gayatri R. Tiwari ◽

Yunlong Liu ◽

Amy Brock ◽

R. Dayne Mayfield

Keyword(s):

Alcohol Dependence ◽

Single Cell ◽

Cell Types ◽

Health Concern ◽

Cell Type ◽

Altered Expression ◽

Cell Transcriptome ◽

Single Cell Transcriptome ◽

The Brain ◽

Alcohol Dependent

AbstractBackgroundAlcoholism remains a prevalent health concern throughout the world. Previous studies have identified transcriptomic patterns in the brain associated with alcohol dependence in both humans and animal models. But none of these studies have systematically investigated expression within the unique cell types present in the brain.ResultsWe utilized single nucleus RNA sequencing (snRNA-seq) to examine the transcriptomes of over 16,000 nuclei isolated from prefrontal cortex of alcoholic and control individuals. Each nucleus was assigned to one of seven major cell types by unsupervised clustering. Cell type enrichment patterns varied greatly among neuroinflammatory-related genes, which are known to play roles in alcohol dependence and neurodegeneration. Differential expression analysis identified cell type-specific genes with altered expression in alcoholics. The largest number of differentially expressed genes (DEGs), including both protein-coding and non-coding, were detected in astrocytes, oligodendrocytes, and microglia.ConclusionsTo our knowledge, this is the first single cell transcriptome analysis of alcohol-associated gene expression in any species, and the first such analysis in humans for any addictive substance. These findings greatly advance understanding of transcriptomic changes in the brain of alcohol-dependent individuals.

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Single-cell regulatory landscape and disease vulnerability map of adult Macaque cortex

10.1101/2020.05.14.087601 ◽

2020 ◽

Author(s):

Ying Lei ◽

Mengnan Cheng ◽

Zihao Li ◽

Zhenkun Zhuang ◽

Liang Wu ◽

...

Keyword(s):

Gene Expression ◽

Single Cell ◽

Primary Motor Cortex ◽

Neurological Diseases ◽

Single Cells ◽

Cell Types ◽

Regulatory Elements ◽

Chromatin Accessibility ◽

Nucleotide Polymorphisms ◽

Cell Type

Non-human primates (NHP) provide a unique opportunity to study human neurological diseases, yet detailed characterization of the cell types and transcriptional regulatory features in the NHP brain is lacking. We applied a combinatorial indexing assay, sci-ATAC-seq, as well as single-nuclei RNA-seq, to profile chromatin accessibility in 43,793 single cells and transcriptomics in 11,477 cells, respectively, from prefrontal cortex, primary motor cortex and the primary visual cortex of adult cynomolgus monkey Macaca fascularis. Integrative analysis of these two datasets, resolved regulatory elements and transcription factors that specify cell type distinctions, and discovered area-specific diversity in chromatin accessibility and gene expression within excitatory neurons. We also constructed the dynamic landscape of chromatin accessibility and gene expression of oligodendrocyte maturation to characterize adult remyelination. Furthermore, we identified cell type-specific enrichment of differentially spliced gene isoforms and disease-associated single nucleotide polymorphisms. Our datasets permit integrative exploration of complex regulatory dynamics in macaque brain tissue at single-cell resolution.

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

10.1101/2020.02.29.970558 ◽

2020 ◽

Cited By ~ 15

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.

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

Nature ◽

10.1038/s41586-021-03950-0 ◽

2021 ◽

Vol 598 (7879) ◽

pp. 86-102 ◽

Cited By ~ 7

Author(s):

◽

Edward M. Callaway ◽

Hong-Wei Dong ◽

Joseph R. Ecker ◽

Michael J. Hawrylycz ◽

...

Keyword(s):

Motor Cortex ◽

Single Cell ◽

Primary Motor Cortex ◽

Spatial Information ◽

Molecular Genetic ◽

Cortical Cell ◽

Neuronal Cell ◽

Open Chromatin ◽

Cell Type ◽

Spatially Resolved

AbstractHere we report the generation of a multimodal cell census and atlas of the mammalian primary motor cortex 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. Our results advance the collective knowledge and understanding of brain cell-type organization1–5. First, our study reveals a unified molecular genetic landscape of cortical cell types that integrates their transcriptome, open chromatin and DNA methylation maps. Second, cross-species analysis achieves a consensus taxonomy of transcriptomic types and their hierarchical organization that is conserved from mouse to marmoset and human. Third, in situ single-cell transcriptomics provides a spatially resolved cell-type atlas of the motor cortex. Fourth, cross-modal analysis provides compelling evidence for the transcriptomic, epigenomic and gene regulatory basis of neuronal phenotypes such as their physiological and anatomical properties, demonstrating the biological validity and genomic underpinning of neuron types. We further present an extensive genetic toolset for targeting glutamatergic neuron types towards linking their molecular and developmental identity to their circuit function. Together, our results establish a unifying and mechanistic framework of neuronal cell-type organization that integrates multi-layered molecular genetic and spatial information with multi-faceted phenotypic properties.

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Parallel RNA and DNA analysis after Deep-sequencing (PRDD-seq) reveals cell type specific lineage patterns in human brain

10.1101/2020.04.19.046904 ◽

2020 ◽

Author(s):

August Yue Huang ◽

Pengpeng Li ◽

Rachel E. Rodin ◽

Sonia N. Kim ◽

Yanmei Dou ◽

...

Keyword(s):

Human Brain ◽

Single Cell ◽

Cell Lineage ◽

Neuronal Cell ◽

Cell Types ◽

Inhibitory Neurons ◽

Cell Type ◽

Cell Divisions ◽

Excitatory Neurons ◽

The Brain

AbstractElucidating the lineage relationships among different cell types is key to understanding human brain development. Here we developed Parallel RNA and DNA analysis after Deep-sequencing (PRDD-seq), which combines RNA analysis of neuronal cell types with analysis of nested spontaneous DNA somatic mutations as cell lineage markers, identified from joint analysis of single cell and bulk DNA sequencing by single-cell MosaicHunter (scMH). PRDD-seq enables the first-ever simultaneous reconstruction of neuronal cell type, cell lineage, and sequential neuronal formation (“birthdate”) in postmortem human cerebral cortex. Analysis of two human brains showed remarkable quantitative details that relate mutation mosaic frequency to clonal patterns, confirming an early divergence of precursors for excitatory and inhibitory neurons, and an “inside-out” layer formation of excitatory neurons as seen in other species. In addition our analysis allows the first estimate of excitatory neuron-restricted precursors (about 10) that generate the excitatory neurons within a cortical column. Inhibitory neurons showed complex, subtype-specific patterns of neurogenesis, including some patterns of development conserved relative to mouse, but also some aspects of primate cortical interneuron development not seen in mouse. PRDD-seq can be broadly applied to characterize cell identity and lineage from diverse archival samples with single-cell resolution and in potentially any developmental or disease condition.Significance StatementStem cells and progenitors undergo a series of cell divisions to generate the neurons of the brain, and understanding this sequence is critical to studying the mechanisms that control cell division and migration in developing brain. Mutations that occur as cells divide are known as the basis of cancer, but have more recently been shown to occur with normal cell divisions, creating a permanent, forensic map of the clonal patterns that define the brain. Here we develop new technology to analyze both DNA mutations and RNA gene expression patterns in single cells from human postmortem brain, allowing us to define clonal patterns among different types of human brain neurons, gaining the first direct insight into how they form.

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