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Author

Ye Zhang

Bio: Ye Zhang is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Astrocyte & Microglia. The author has an hindex of 15, co-authored 24 publications receiving 7341 citations. Previous affiliations of Ye Zhang include Semel Institute for Neuroscience and Human Behavior & Stanford University.
Topics: Astrocyte, Microglia, Medicine, Biology, Transcriptome

Papers
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Journal ArticleDOI
TL;DR: The authors' data provide clues as to how neurons and astrocytes differ in their ability to dynamically regulate glycolytic flux and lactate generation attributable to unique splicing of PKM2, the gene encoding the glycoleytic enzyme pyruvate kinase.
Abstract: The major cell classes of the brain differ in their developmental processes, metabolism, signaling, and function To better understand the functions and interactions of the cell types that comprise these classes, we acutely purified representative populations of neurons, astrocytes, oligodendrocyte precursor cells, newly formed oligodendrocytes, myelinating oligodendrocytes, microglia, endothelial cells, and pericytes from mouse cerebral cortex We generated a transcriptome database for these eight cell types by RNA sequencing and used a sensitive algorithm to detect alternative splicing events in each cell type Bioinformatic analyses identified thousands of new cell type-enriched genes and splicing isoforms that will provide novel markers for cell identification, tools for genetic manipulation, and insights into the biology of the brain For example, our data provide clues as to how neurons and astrocytes differ in their ability to dynamically regulate glycolytic flux and lactate generation attributable to unique splicing of PKM2, the gene encoding the glycolytic enzyme pyruvate kinase This dataset will provide a powerful new resource for understanding the development and function of the brain To ensure the widespread distribution of these datasets, we have created a user-friendly website (http://webstanfordedu/group/barres_lab/brain_rnaseqhtml) that provides a platform for analyzing and comparing transciption and alternative splicing profiles for various cell classes in the brain

3,891 citations

Journal ArticleDOI
06 Jan 2016-Neuron
TL;DR: The development of an immunopanning method to acutely purify astrocytes from fetal, juvenile, and adult human brains and to maintain these cells in serum-free cultures is reported, finding that human astroCytes have abilities similar to those of murine astroicytes in promoting neuronal survival, inducing functional synapse formation, and engulfing synaptosomes.

1,593 citations

Journal ArticleDOI
TL;DR: 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.

1,121 citations

Journal ArticleDOI
TL;DR: Despite the existence of significant heterogeneity among neoplastic cells, it is found that infiltrating GBM cells share a consistent gene signature between patients, suggesting a common mechanism of infiltration.

602 citations

Journal ArticleDOI
TL;DR: Evidence has accumulated that suggests heterogeneity of astrocytes across brain regions as well as within the same brain regions, which will greatly aid investigation of the function of astracytes in normal brain aswell as the roles of astrospecies in neurological disorders.

492 citations


Cited by
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Journal ArticleDOI
26 Jan 2017-Nature
TL;DR: It is shown that activated microglia induce A1 astrocytes by secreting Il-1α, TNF and C1q, and that these cytokines together are necessary and sufficient to induce A2 astroCytes, which are abundant in various human neurodegenerative diseases.
Abstract: This work was supported by grants from the National Institutes of Health (R01 AG048814, B.A.B.; RO1 DA15043, B.A.B.; P50 NS38377, V.L.D. and T.M.D.) Christopher and Dana Reeve Foundation (B.A.B.), the Novartis Institute for Biomedical Research (B.A.B.), Dr. Miriam and Sheldon G. Adelson Medical Research Foundation (B.A.B.), the JPB Foundation (B.A.B., T.M.D.), the Cure Alzheimer’s Fund (B.A.B.), the Glenn Foundation (B.A.B.), the Esther B O’Keeffe Charitable Foundation (B.A.B.), the Maryland Stem Cell Research Fund (2013-MSCRFII-0105-00, V.L.D.; 2012-MSCRFII-0268-00, T.M.D.; 2013-MSCRFII-0105-00, T.M.D.; 2014-MSCRFF-0665, M.K.). S.A.L. was supported by a postdoctoral fellowship from the Australian National Health and Medical Research Council (GNT1052961), and the Glenn Foundation Glenn Award. L.E.C. was funded by a Merck Research Laboratories postdoctoral fellowship (administered by the Life Science Research Foundation). W.-S.C. was supported by a career transition grant from NEI (K99EY024690). C.J.B. was supported by a postdoctoral fellowship from Damon Runyon Cancer Research Foundation (DRG-2125-12). L.S. was supported by a postdoctoral fellowship from the German Research Foundation (DFG, SCHI 1330/1-1).

4,326 citations

01 Jan 2013
TL;DR: In this article, the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs) was described, including several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA.
Abstract: We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

2,616 citations

Journal ArticleDOI
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.
Abstract: We present SCENIC, a computational method for simultaneous gene regulatory network reconstruction and cell-state identification from single-cell RNA-seq data (http://scenicaertslaborg) On a compendium of single-cell data from tumors and brain, we demonstrate that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity

2,277 citations

Journal ArticleDOI
18 Oct 2018-Nature
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.
Abstract: Here we present 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. These data represent a new resource for cell biology, reveal gene expression in poorly characterized cell populations and enable the direct and controlled comparison of gene expression in cell types that are shared between tissues, such as T lymphocytes and endothelial cells from different anatomical locations. Two distinct technical approaches were used for most organs: one approach, microfluidic droplet-based 3'-end counting, enabled the survey of thousands of cells at relatively low coverage, whereas the other, full-length transcript analysis based on fluorescence-activated cell sorting, enabled the characterization of cell types with high sensitivity and coverage. The cumulative data provide the foundation for an atlas of transcriptomic cell biology.

1,757 citations

Journal ArticleDOI
TL;DR: Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer’s disease but also with LOAD.
Abstract: Risk for late-onset Alzheimer’s disease (LOAD), the most prevalent dementia, is partially driven by genetics. To identify LOAD risk loci, we performed a large genome-wide association meta-analysis of clinically diagnosed LOAD (94,437 individuals). We confirm 20 previous LOAD risk loci and identify five new genome-wide loci (IQCK, ACE, ADAM10, ADAMTS1, and WWOX), two of which (ADAM10, ACE) were identified in a recent genome-wide association (GWAS)-by-familial-proxy of Alzheimer’s or dementia. Fine-mapping of the human leukocyte antigen (HLA) region confirms the neurological and immune-mediated disease haplotype HLA-DR15 as a risk factor for LOAD. Pathway analysis implicates immunity, lipid metabolism, tau binding proteins, and amyloid precursor protein (APP) metabolism, showing that genetic variants affecting APP and Aβ processing are associated not only with early-onset autosomal dominant Alzheimer’s disease but also with LOAD. Analyses of risk genes and pathways show enrichment for rare variants (P = 1.32 × 10−7), indicating that additional rare variants remain to be identified. We also identify important genetic correlations between LOAD and traits such as family history of dementia and education.

1,641 citations