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Open AccessJournal ArticleDOI

A survey of human brain transcriptome diversity at the single cell level

TLDR
The first, to the authors' knowledge, single cell whole transcriptome analysis of human adult cortical samples is described, establishing an experimental and analytical framework with which the complexity of the human brain can be dissected on the single cell level.
Abstract
The human brain is a tissue of vast complexity in terms of the cell types it comprises. Conventional approaches to classifying cell types in the human brain at single cell resolution have been limited to exploring relatively few markers and therefore have provided a limited molecular characterization of any given cell type. We used single cell RNA sequencing on 466 cells to capture the cellular complexity of the adult and fetal human brain at a whole transcriptome level. Healthy adult temporal lobe tissue was obtained during surgical procedures where otherwise normal tissue was removed to gain access to deeper hippocampal pathology in patients with medical refractory seizures. We were able to classify individual cells into all of the major neuronal, glial, and vascular cell types in the brain. We were able to divide neurons into individual communities and show that these communities preserve the categorization of interneuron subtypes that is typically observed with the use of classic interneuron markers. We then used single cell RNA sequencing on fetal human cortical neurons to identify genes that are differentially expressed between fetal and adult neurons and those genes that display an expression gradient that reflects the transition between replicating and quiescent fetal neuronal populations. Finally, we observed the expression of major histocompatibility complex type I genes in a subset of adult neurons, but not fetal neurons. The work presented here demonstrates the applicability of single cell RNA sequencing on the study of the adult human brain and constitutes a first step toward a comprehensive cellular atlas of the human brain.

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Citations
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Journal ArticleDOI

SCENIC: single-cell regulatory network inference and clustering.

TL;DR: On a compendium of single-cell data from tumors and brain, it is demonstrated that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states.
Journal ArticleDOI

Single-cell transcriptomics of 20 mouse organs creates a "Tabula Muris"

TL;DR: A compendium of single-cell transcriptomic data from the model organism Mus musculus that comprises more than 100,000 cells from 20 organs and tissues is presented, representing a new resource for cell biology and enabling the direct and controlled comparison of gene expression in cell types that are shared between tissues.
Journal ArticleDOI

The Human Cell Atlas

Aviv Regev, +81 more
- 05 Dec 2017 - 
TL;DR: An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease.
Journal ArticleDOI

The Cellular Phase of Alzheimer’s Disease

TL;DR: Evidence supporting a long, complex cellular phase consisting of feedback and feedforward responses of astrocytes, microglia, and vasculature is reviewed.
Journal ArticleDOI

An Integrative Model of Cellular States, Plasticity, and Genetics for Glioblastoma

TL;DR: It is found that malignant cells in glioblastoma exist in four main cellular states that recapitulate distinct neural cell types, are influenced by the tumor microenvironment, and exhibit plasticity.
References
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Journal ArticleDOI

A transcriptome database for astrocytes, neurons, and oligodendrocytes: a new resource for understanding brain development and function.

TL;DR: These findings call into question the concept of a “glial” cell class as the gene profiles of astrocyte and oligodendrocytes are as dissimilar to each other as they are to neurons, for better understanding of neural development, function, and disease.
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Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq

TL;DR: Large-scale single-cell RNA sequencing is used to classify cells in the mouse somatosensory cortex and hippocampal CA1 region and found 47 molecularly distinct subclasses, comprising all known major cell types in the cortex.
Journal ArticleDOI

Reconstructing lineage hierarchies of the distal lung epithelium using single cell RNA-seq

TL;DR: The results confirmed the basic outlines of the classical model of epithelial cell-type diversity in the distal lung and led to the discovery of many previously unknown cell- type markers, including transcriptional regulators that discriminate between the different populations.
Journal ArticleDOI

Three groups of interneurons account for nearly 100% of neocortical GABAergic neurons

TL;DR: The universal modulation of these neurons by serotonin and acetylcholine via ionotropic receptors suggests that they might be involved in shaping cortical circuits during specific brain states andbehavioral contexts.
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