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Journal Article•DOI•

An RNA-Sequencing Transcriptome and Splicing Database of Glia, Neurons, and Vascular Cells of the Cerebral Cortex

Ye Zhang1, Kenian Chen2, Steven A. Sloan1, Mariko L. Bennett1, Anja R. Scholze1, Sean O'Keeffe3, Hemali Phatnani3, Paolo Guarnieri4, Christine Caneda1, Nadine Ruderisch5, Shuyun Deng2, Shane A. Liddelow1, Chaolin Zhang3, Richard Daneman5, Tom Maniatis3, Ben A. Barres1, Jian Qian Wu2 •
Stanford University1, University of Texas at Austin2, Columbia University Medical Center3, Columbia University4, University of California, San Francisco5
03 Sep 2014-The Journal of Neuroscience (Society for Neuroscience)-Vol. 34, Iss: 36, pp 11929-11947
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
Citations
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Journal Article•DOI•
Neurotoxic reactive astrocytes are induced by activated microglia

[...]

Shane A. Liddelow1, Kevin A. Guttenplan1, Laura E. Clarke1, Frederick C. Bennett1, Christopher J. Bohlen2, Lucas Schirmer3, Mariko L. Bennett1, Alexandra E. Münch1, Won-Suk Chung4, Todd C. Peterson1, Daniel K. Wilton5, Arnaud Frouin5, Brooke A. Napier1, Nikhil Panicker6, Manoj Kumar6, Marion S. Buckwalter1, David H. Rowitch3, Valina L. Dawson, Ted M. Dawson, Beth Stevens5, Ben A. Barres1 •
Stanford University1, University of Melbourne2, University of California, San Francisco3, KAIST4, Boston Children's Hospital5, Johns Hopkins University School of Medicine6
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

Journal Article•DOI•
Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing

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Cohorts for Heart1, Genetic2, Genetic3, Genetic4, Environmental Risk in Ad, Polygenic Defining Genetic, Perades5 •
Cardiff University1, university of lille2, Pasteur Institute3, French Institute of Health and Medical Research4, Erasmus University Rotterdam5
01 Mar 2019-Nature Genetics
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

Journal Article•DOI•
Purification and Characterization of Progenitor and Mature Human Astrocytes Reveals Transcriptional and Functional Differences with Mouse.

[...]

Ye Zhang1, Steven A. Sloan1, Laura E. Clarke1, Christine Caneda1, Colton A. Plaza1, Paul D. Blumenthal1, Hannes Vogel1, Gary K. Steinberg2, Michael S. B. Edwards2, Gordon Li2, John A. Duncan3, Samuel H. Cheshier2, Lawrence M. Shuer2, Edward F. Chang4, Gerald A. Grant2, Melanie Hayden Gephart2, Ben A. Barres1 •
Stanford University1, Lucile Packard Children's Hospital2, Kaiser Permanente3, University of California, San Francisco4
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

Cites methods from "An RNA-Sequencing Transcriptome and..."

  • ...We mined our existing mouse astrocyte RNA sequencing (RNA-seq) datasets (Zhang et al., 2014) for potential surface markers that were enriched in astrocytes, not expressed by radial glial cells (a major cellular constituent of fetal human brain), and where antibodies to the human antigen already…...

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  • ...We mined our existing mouse astrocyte RNA sequencing (RNA-seq) datasets (Zhang et al., 2014) for potential surface markers that were enriched in astrocytes, not expressed by radial glial cells (a major cellular constituent of fetal human brain), and where antibodies to the human antigen already existed....

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  • ...RNA-seq data from mouse astrocytes were previously collected by FACS from transgenic lines (Zhang et al., 2014), we collected new mouse astrocyte samples using an identical procedure to our human astrocytes, including the use of the monoclonal HepaCAM antibody for immunopanning....

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  • ...Digoxigenin (DIG)-labeled single-stranded antisense riboprobes were prepared, and fresh-frozen 12-mm-thick brain sections were processed as previously described (Zhang et al., 2014) (Supplemental Information)....

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Journal Article•DOI•
Adult mouse cortical cell taxonomy revealed by single cell transcriptomics

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Bosiljka Tasic1, Vilas Menon1, Thuc Nghi Nguyen1, Tae Kyung Kim1, Tim Jarsky1, Zizhen Yao1, Boaz P. Levi1, Lucas T. Gray1, Staci A. Sorensen1, Tim A. Dolbeare1, Darren Bertagnolli1, Jeff Goldy1, Nadiya V. Shapovalova1, Sheana Parry1, Changkyu Lee1, Kimberly A. Smith1, Amy Bernard1, Linda Madisen1, Susan M. Sunkin1, Michael Hawrylycz1, Christof Koch1, Hongkui Zeng1 •
Allen Institute for Brain Science1
01 Feb 2016-Nature Neuroscience
TL;DR: This work constructed a cellular taxonomy of one cortical region, primary visual cortex, in adult mice on the basis of single-cell RNA sequencing and identified 49 transcriptomic cell types, including 23 GABAergic, 19 glutamatergic and 7 non-neuronal types.
Abstract: Nervous systems are composed of various cell types, but the extent of cell type diversity is poorly understood. We constructed a cellular taxonomy of one cortical region, primary visual cortex, in adult mice on the basis of single-cell RNA sequencing. We identified 49 transcriptomic cell types, including 23 GABAergic, 19 glutamatergic and 7 non-neuronal types. We also analyzed cell type-specific mRNA processing and characterized genetic access to these transcriptomic types by many transgenic Cre lines. Finally, we found that some of our transcriptomic cell types displayed specific and differential electrophysiological and axon projection properties, thereby confirming that the single-cell transcriptomic signatures can be associated with specific cellular properties.

1,388 citations

Journal Article•DOI•
New tools for studying microglia in the mouse and human CNS.

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Mariko L. Bennett1, F. Chris Bennett1, Shane A. Liddelow2, Shane A. Liddelow1, Bahareh Ajami1, Jennifer L. Zamanian1, Nathaniel B. Fernhoff, Sara B. Mulinyawe1, Christopher J. Bohlen1, Aykezar Adil1, Andrew Tucker1, Irving L. Weissman, Edward F. Chang3, Gordon Li1, Gerald A. Grant1, Melanie Hayden Gephart1, Ben A. Barres1 •
Stanford University1, University of Melbourne2, University of California, San Francisco3
22 Mar 2016-Proceedings of the National Academy of Sciences of the United States of America
TL;DR: Transmembrane protein 119 (Tmem119), a cell-surface protein of unknown function, is identified as a highly expressed microglia-specific marker in both mouse and human, which will greatly facilitate understanding of microglial function in health and disease.
Abstract: The specific function of microglia, the tissue resident macrophages of the brain and spinal cord, has been difficult to ascertain because of a lack of tools to distinguish microglia from other immune cells, thereby limiting specific immunostaining, purification, and manipulation. Because of their unique developmental origins and predicted functions, the distinction of microglia from other myeloid cells is critically important for understanding brain development and disease; better tools would greatly facilitate studies of microglia function in the developing, adult, and injured CNS. Here, we identify transmembrane protein 119 (Tmem119), a cell-surface protein of unknown function, as a highly expressed microglia-specific marker in both mouse and human. We developed monoclonal antibodies to its intracellular and extracellular domains that enable the immunostaining of microglia in histological sections in healthy and diseased brains, as well as isolation of pure nonactivated microglia by FACS. Using our antibodies, we provide, to our knowledge, the first RNAseq profiles of highly pure mouse microglia during development and after an immune challenge. We used these to demonstrate that mouse microglia mature by the second postnatal week and to predict novel microglial functions. Together, we anticipate these resources will be valuable for the future study and understanding of microglia in health and disease.

1,299 citations

Cites methods from "An RNA-Sequencing Transcriptome and..."

  • ...We calculated percentile ranks for several canonical activation genes for our naïve and LPS-stimulated samples, as well as five published datasets (15, 17, 30, 33, 34); these datasets were generated using CD45 or Cx3cr1 rather than a specific microglia marker, such as Tmem119, and used enzymatic digestion or Percoll for dissociation and myelin depletion....

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  • ...Given our interest in Tmem119 expression patterns and microglial maturity, we performed unsupervised hierarchical clustering of our microglial and published RNAseq datasets (30) to find other similarly behaved genes (SI Appendix, Table S3 and Dataset S1, “clusterID” column)....

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References
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Journal Article•DOI•
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome

[...]

Ben Langmead1, Cole Trapnell1, Mihai Pop1, Steven L. Salzberg1•
University of Maryland, College Park1
04 Mar 2009-Genome Biology
TL;DR: Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches and can be used simultaneously to achieve even greater alignment speeds.
Abstract: Bowtie is an ultrafast, memory-efficient alignment program for aligning short DNA sequence reads to large genomes. For the human genome, Burrows-Wheeler indexing allows Bowtie to align more than 25 million reads per CPU hour with a memory footprint of approximately 1.3 gigabytes. Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches. Multiple processor cores can be used simultaneously to achieve even greater alignment speeds. Bowtie is open source http://bowtie.cbcb.umd.edu.

20,335 citations

"An RNA-Sequencing Transcriptome and..." refers methods in this paper

  • ...…100 bp paired-end reads to the mouse reference genome [University of California, Santa Cruz (UCSC) Genome Browser version mm9] was performed using TopHat software (version 1.3.3; Trapnell et al., 2010), which invokes Bowtie (version 0.12.7) as an internal read mapper (Langmead et al., 2009)....

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Journal Article•DOI•
Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation

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Cole Trapnell1, Cole Trapnell2, Brian A. Williams3, Geo Pertea1, Ali Mortazavi3, Gordon Kwan3, Marijke J. van Baren4, Steven L. Salzberg1, Barbara J. Wold3, Lior Pachter2 •
University of Maryland, College Park1, University of California, Berkeley2, California Institute of Technology3, Washington University in St. Louis4
01 May 2010-Nature Biotechnology
TL;DR: The results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.
Abstract: High-throughput mRNA sequencing (RNA-Seq) promises simultaneous transcript discovery and abundance estimation. However, this would require algorithms that are not restricted by prior gene annotations and that account for alternative transcription and splicing. Here we introduce such algorithms in an open-source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed >430 million paired 75-bp RNA-Seq reads from a mouse myoblast cell line over a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Over the time series, 330 genes showed complete switches in the dominant transcription start site (TSS) or splice isoform, and we observed more subtle shifts in 1,304 other genes. These results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.

13,337 citations

"An RNA-Sequencing Transcriptome and..." refers background or methods in this paper

  • ...…100 bp paired-end reads to the mouse reference genome [University of California, Santa Cruz (UCSC) Genome Browser version mm9] was performed using TopHat software (version 1.3.3; Trapnell et al., 2010), which invokes Bowtie (version 0.12.7) as an internal read mapper (Langmead et al., 2009)....

    [...]

  • ...After read mapping, transcripts were then assembled using Cufflinks software (version 1.3.0; Trapnell et al., 2010)....

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  • ...We then recalculated expression levels with Cufflinks using the amended annotation file and extracted corresponding FPKM values for lncRNAs....

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  • ...To correct for these biases, we adopted the widely accepted Cufflinks algorithm to estimate FPKM values....

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  • ...…in lower falsenegative and false-positive discovery rates in addition to a greater linear range (Bainbridge et al., 2006; Cloonan et al., 2008; Marioni et al., 2008; Mortazavi et al., 2008; Nagalakshmi et al., 2008; Sultan et al., 2008; Wilhelm et al., 2008; Trapnell et al., 2010; Wu et al., 2010)....

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Journal Article•DOI•
Mapping and quantifying mammalian transcriptomes by RNA-Seq.

[...]

Ali Mortazavi1, Brian A. Williams1, Kenneth McCue1, Lorian Schaeffer1, Barbara J. Wold1 •
California Institute of Technology1
29 Jun 2008-Nature Methods
TL;DR: Although >90% of uniquely mapped reads fell within known exons, the remaining data suggest new and revised gene models, including changed or additional promoters, exons and 3′ untranscribed regions, as well as new candidate microRNA precursors.
Abstract: We have mapped and quantified mouse transcriptomes by deeply sequencing them and recording how frequently each gene is represented in the sequence sample (RNA-Seq). This provides a digital measure of the presence and prevalence of transcripts from known and previously unknown genes. We report reference measurements composed of 41–52 million mapped 25-base-pair reads for poly(A)-selected RNA from adult mouse brain, liver and skeletal muscle tissues. We used RNA standards to quantify transcript prevalence and to test the linear range of transcript detection, which spanned five orders of magnitude. Although >90% of uniquely mapped reads fell within known exons, the remaining data suggest new and revised gene models, including changed or additional promoters, exons and 3′ untranscribed regions, as well as new candidate microRNA precursors. RNA splice events, which are not readily measured by standard gene expression microarray or serial analysis of gene expression methods, were detected directly by mapping splice-crossing sequence reads. We observed 1.45 × 10 5 distinct splices, and alternative splices were prominent, with 3,500 different genes expressing one or more alternate internal splices. The mRNA population specifies a cell’s identity and helps to govern its present and future activities. This has made transcriptome analysis a general phenotyping method, with expression microarrays of many kinds in routine use. Here we explore the possibility that transcriptome analysis, transcript discovery and transcript refinement can be done effectively in large and complex mammalian genomes by ultra-high-throughput sequencing. Expression microarrays are currently the most widely used methodology for transcriptome analysis, although some limitations persist. These include hybridization and cross-hybridization artifacts 1–3 , dye-based detection issues and design constraints that preclude or seriously limit the detection of RNA splice patterns and previously unmapped genes. These issues have made it difficult for standard array designs to provide full sequence comprehensiveness (coverage of all possible genes, including unknown ones, in large genomes) or transcriptome comprehensiveness (reliable detection of all RNAs of all prevalence classes, including the least abundant ones that are physiologically relevant). Other

12,293 citations

"An RNA-Sequencing Transcriptome and..." refers background in this paper

  • ...…in lower falsenegative and false-positive discovery rates in addition to a greater linear range (Bainbridge et al., 2006; Cloonan et al., 2008; Marioni et al., 2008; Mortazavi et al., 2008; Nagalakshmi et al., 2008; Sultan et al., 2008; Wilhelm et al., 2008; Trapnell et al., 2010; Wu et al., 2010)....

    [...]

  • ...Transcript abundance is directly proportional to the number of sequencing reads that map to a specific transcript, resulting in lower falsenegative and false-positive discovery rates in addition to a greater linear range (Bainbridge et al., 2006; Cloonan et al., 2008; Marioni et al., 2008; Mortazavi et al., 2008; Nagalakshmi et al., 2008; Sultan et al., 2008; Wilhelm et al., 2008; Trapnell et al., 2010; Wu et al., 2010)....

    [...]

  • ...Comparing these two technologies, RNA-Seq is believed to have increased sensitivity, improved linearity, and a vastly larger dynamic range (Marioni et al., 2008; Mortazavi et al., 2008; Wang et al., 2009)....

    [...]

Journal Article•DOI•
RNA-Seq: a revolutionary tool for transcriptomics

[...]

Zhong Wang1, Mark Gerstein1, Michael Snyder1•
Yale University1
01 Jan 2009-Nature Reviews Genetics
TL;DR: The RNA-Seq approach to transcriptome profiling that uses deep-sequencing technologies provides a far more precise measurement of levels of transcripts and their isoforms than other methods.
Abstract: RNA-Seq is a recently developed approach to transcriptome profiling that uses deep-sequencing technologies. Studies using this method have already altered our view of the extent and complexity of eukaryotic transcriptomes. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods. This article describes the RNA-Seq approach, the challenges associated with its application, and the advances made so far in characterizing several eukaryote transcriptomes.

11,528 citations

"An RNA-Sequencing Transcriptome and..." refers background in this paper

  • ...Comparing these two technologies, RNA-Seq is believed to have increased sensitivity, improved linearity, and a vastly larger dynamic range (Marioni et al., 2008; Mortazavi et al., 2008; Wang et al., 2009)....

    [...]

Journal Article•DOI•
Long non-coding RNAs: insights into functions

[...]

Tim R. Mercer1, Marcel E. Dinger1, John S. Mattick1•
University of Queensland1
01 Mar 2009-Nature Reviews Genetics
TL;DR: The rapidly advancing field of long ncRNAs is reviewed, describing their conservation, their organization in the genome and their roles in gene regulation, and the medical implications.
Abstract: In mammals and other eukaryotes most of the genome is transcribed in a developmentally regulated manner to produce large numbers of long non-coding RNAs (ncRNAs). Here we review the rapidly advancing field of long ncRNAs, describing their conservation, their organization in the genome and their roles in gene regulation. We also consider the medical implications, and the emerging recognition that any transcript, regardless of coding potential, can have an intrinsic function as an RNA.

4,911 citations

"An RNA-Sequencing Transcriptome and..." refers background in this paper

  • ...However, the expression landscape of lncRNAs across different cell types has not been characterized in a complex organ such as the brain....

    [...]

  • ...The eukaryotic genome is transcribed in a developmentally regulated manner to produce large numbers of lncRNA or large intervening noncoding RNAs (Guttman et al., 2009; Mercer et al., 2009), the function of which in gene regulation and cancer pathogenesis are increasingly being recognized....

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  • ...DOI:10.1523/JNEUROSCI.1860-14.2014 Copyright © 2014 the authors 0270-6474/14/3411929-19$15.00/0 RNA sequencing (RNA-Seq) is a method that profiles the transcriptome by deep sequencing of isolated RNAs....

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  • ...One possibility is the presence of distinct RNA granules containing Gdpd2 and Glast mRNAs within astrocytes....

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  • ...Some lncRNAs are expressed in cell type-specific or enriched manners (Table 1)....

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Related Papers (5)
STAR: ultrafast universal RNA-seq aligner

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01 Jan 2013-Bioinformatics
Alexander Dobin, Carrie A. Davis, Felix Schlesinger, Jorg Drenkow, Chris Zaleski, Sonali Jha, Philippe Batut, Mark Chaisson, Thomas R. Gingeras 
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

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05 Dec 2014-Genome Biology
Michael I. Love, Michael I. Love, Wolfgang Huber, Simon Anders 
Neurotoxic reactive astrocytes are induced by activated microglia

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26 Jan 2017-Nature
Shane A. Liddelow, Kevin A. Guttenplan, Laura E. Clarke, Frederick C. Bennett, Christopher J. Bohlen, Lucas Schirmer, Mariko L. Bennett, Alexandra E. Münch, Won-Suk Chung, Todd C. Peterson, Daniel K. Wilton, Arnaud Frouin, Brooke A. Napier, Nikhil Panicker, Manoj Kumar, Marion S. Buckwalter, David H. Rowitch, Valina L. Dawson, Ted M. Dawson, Beth Stevens, Ben A. Barres 
Resting Microglial Cells Are Highly Dynamic Surveillants of Brain Parenchyma in Vivo

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27 May 2005-Science
Axel Nimmerjahn, Frank Kirchhoff, Fritjof Helmchen
Microglia sculpt postnatal neural circuits in an activity and complement-dependent manner.

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24 May 2012-Neuron
Dorothy P. Schafer, Emily K. Lehrman, Amanda G. Kautzman, Ryuta Koyama, Alan R. Mardinly, Ryo Yamasaki, Richard M. Ransohoff, Michael E. Greenberg, Ben A. Barres, Beth Stevens