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den Berge KV, Chou HJ, Kunda D, Risso D, Street K, Purdom E, Dudoit S, Ngai J, Heavner W. A Latent Activated Olfactory Stem Cell State Revealed by Single Cell Transcriptomic and Epigenomic Profiling. bioRxiv 2023:2023.10.26.564041. [PMID: 37961539 PMCID: PMC10634988 DOI: 10.1101/2023.10.26.564041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The olfactory epithelium is one of the few regions of the nervous system that sustains neurogenesis throughout life. Its experimental accessibility makes it especially tractable for studying molecular mechanisms that drive neural regeneration after injury-induced cell death. In this study, we used single cell sequencing to identify major regulatory players in determining olfactory epithelial stem cell fate after acute injury. We combined gene expression and accessible chromatin profiles of individual lineage traced olfactory stem cells to predict transcription factor activity specific to different lineages and stages of recovery. We further identified a discrete stem cell state that appears poised for activation, characterized by accessible chromatin around wound response and lineage specific genes prior to their later expression in response to injury. Together these results provide evidence that a subset of quiescent olfactory epithelial stem cells are epigenetically primed to support injury-induced regeneration.
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Affiliation(s)
| | - Hsin-Jung Chou
- Department of Molecular and Cell Biology, University of California, Berkeley, CA
| | - Divya Kunda
- Molecular Neurobiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Davide Risso
- Department of Statistical Sciences, University of Padova, Padova, Italy
| | - Kelly Street
- Division of Biostatistics, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Elizabeth Purdom
- Department of Statistics, University of California, Berkeley, CA
| | - Sandrine Dudoit
- Department of Statistics, University of California, Berkeley, CA
- Division of Biostatistics, School of Public Health, University of California, Berkeley, CA
| | - John Ngai
- Molecular Neurobiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
| | - Whitney Heavner
- Molecular Neurobiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
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2
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Hendriks S, Hsu N, Beckel-Mitchener AC, Ngai J, Grady C. Continuing trial responsibilities for implantable neural devices. Neuron 2023; 111:3143-3149. [PMID: 37582365 DOI: 10.1016/j.neuron.2023.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 06/27/2023] [Accepted: 07/12/2023] [Indexed: 08/17/2023]
Abstract
Participants of neural implant studies have research-related posttrial care needs (e.g., hardware replacements). Gaps in plans for posttrial care are currently common, which can have major consequences for patients. Professionals and organizations involved should address important unmet posttrial needs.
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Affiliation(s)
- Saskia Hendriks
- Office of Neuroscience Communications and Engagement, NINDS, NIH, Bethesda, MD, USA; Department of Bioethics, NIH Clinical Center, Bethesda, MD, USA.
| | - Nina Hsu
- Office of Neuroscience Communications and Engagement, NINDS, NIH, Bethesda, MD, USA
| | | | - John Ngai
- NIH BRAIN Initiative, NIH, Bethesda, MD, USA
| | - Christine Grady
- Department of Bioethics, NIH Clinical Center, Bethesda, MD, USA
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3
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Moazami N, Smith D, Stern J, Kim J, Khalil K, James L, Kowalski H, Bisen S, Bamira D, Saraon T, Reyentovich A, Piper G, Sommer P, Ngai J, Mangiola M, Mehta S, Griesemer A, Ayares D, Narula N, Weldon E, Montgomery R. Two 10-Gene Modified Xenoheart Transplants into Brain Dead Decedents. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.1507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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4
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Chang S, Piper G, Chan J, Geraci T, Hsiung T, James L, Ngai J, Natalini J, Rudym D, Lesko M, Hussain S, Reyentovich A, Moazami N, Smith D, Angel L. Lung Transplantation Utilizing Donor after Circulatory Death with Normothermic Regional Perfusion. J Heart Lung Transplant 2023. [DOI: 10.1016/j.healun.2023.02.1027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023] Open
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5
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Van den Berge K, Chou HJ, Roux de Bézieux H, Street K, Risso D, Ngai J, Dudoit S. Normalization benchmark of ATAC-seq datasets shows the importance of accounting for GC-content effects. Cell Rep Methods 2022; 2:100321. [PMID: 36452861 PMCID: PMC9701614 DOI: 10.1016/j.crmeth.2022.100321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 02/23/2022] [Accepted: 10/06/2022] [Indexed: 06/17/2023]
Abstract
The assay for transposase-accessible chromatin using sequencing (ATAC-seq) allows the study of epigenetic regulation of gene expression by assessing chromatin configuration for an entire genome. Despite its popularity, there have been limited studies investigating the analytical challenges related to ATAC-seq data, with most studies leveraging tools developed for bulk transcriptome sequencing. Here, we show that GC-content effects are omnipresent in ATAC-seq datasets. Since the GC-content effects are sample specific, they can bias downstream analyses such as clustering and differential accessibility analysis. We introduce a normalization method based on smooth-quantile normalization within GC-content bins and evaluate it together with 11 different normalization procedures on 8 public ATAC-seq datasets. Accounting for GC-content effects in the normalization is crucial for common downstream ATAC-seq data analyses, improving accuracy and interpretability. Through case studies, we show that exploratory data analysis is essential to guide the choice of an appropriate normalization method for a given dataset.
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Affiliation(s)
- Koen Van den Berge
- Department of Statistics, University of California, Berkeley, Berkeley, CA, USA
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
- Bioinformatics Institute Ghent, Ghent University, Ghent, Belgium
| | - Hsin-Jung Chou
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Hector Roux de Bézieux
- Division of Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, CA, USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Kelly Street
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Davide Risso
- Department of Statistical Sciences, University of Padova, Padova, Italy
| | - John Ngai
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Sandrine Dudoit
- Department of Statistics, University of California, Berkeley, Berkeley, CA, USA
- Division of Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, CA, USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA, USA
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6
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Abstract
The NIH BRAIN Initiative is entering a new phase. Three large new projects-a comprehensive human brain cell atlas, a whole mammalian brain microconnectivity map, and tools for precision access to brain cell types-promise to transform neuroscience research and the treatment of human brain disorders.
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Affiliation(s)
- John Ngai
- NIH BRAIN Initiative, National Institutes of Health, Bethesda, MD, USA.
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7
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Quaglio G, Toia P, Moser EI, Karapiperis T, Amunts K, Okabe S, Poo MM, Rah JC, Koninck YD, Ngai J, Richards L, Bjaalie JG. The International Brain Initiative: enabling collaborative science. Lancet Neurol 2021; 20:985-986. [PMID: 34800415 DOI: 10.1016/s1474-4422(21)00389-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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8
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Abstract
Leveraging breadth and depth of the scientific workforce invites creativity, relevance, and differing views that directly tie into innovation and problem solving. The NIH BRAIN Initiative is using a multi-pronged strategy to enhance diversity and inclusion toward promoting the best science.
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Affiliation(s)
- Ryan R Richardson
- NIH BRAIN Initiative, National Institutes of Health, Bethesda, MD, USA
| | - Devon C Crawford
- NIH BRAIN Initiative, National Institutes of Health, Bethesda, MD, USA
| | - John Ngai
- NIH BRAIN Initiative, National Institutes of Health, Bethesda, MD, USA.
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9
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Yao Z, Liu H, Xie F, Fischer S, Adkins RS, Aldridge AI, Ament SA, Bartlett A, Behrens MM, Van den Berge K, Bertagnolli D, de Bézieux HR, Biancalani T, Booeshaghi AS, Bravo HC, Casper T, Colantuoni C, Crabtree J, Creasy H, Crichton K, Crow M, Dee N, Dougherty EL, Doyle WI, Dudoit S, Fang R, Felix V, Fong O, Giglio M, Goldy J, Hawrylycz M, Herb BR, Hertzano R, Hou X, Hu Q, Kancherla J, Kroll M, Lathia K, Li YE, Lucero JD, Luo C, Mahurkar A, McMillen D, Nadaf NM, Nery JR, Nguyen TN, Niu SY, Ntranos V, Orvis J, Osteen JK, Pham T, Pinto-Duarte A, Poirion O, Preissl S, Purdom E, Rimorin C, Risso D, Rivkin AC, Smith K, Street K, Sulc J, Svensson V, Tieu M, Torkelson A, Tung H, Vaishnav ED, Vanderburg CR, van Velthoven C, Wang X, White OR, Huang ZJ, Kharchenko PV, Pachter L, Ngai J, Regev A, Tasic B, Welch JD, Gillis J, Macosko EZ, Ren B, Ecker JR, Zeng H, Mukamel EA. A transcriptomic and epigenomic cell atlas of the mouse primary motor cortex. Nature 2021; 598:103-110. [PMID: 34616066 PMCID: PMC8494649 DOI: 10.1038/s41586-021-03500-8] [Citation(s) in RCA: 113] [Impact Index Per Article: 37.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 03/26/2021] [Indexed: 12/30/2022]
Abstract
Single-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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Affiliation(s)
- Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Fangming Xie
- Department of Physics, University of California, San Diego, La Jolla, CA, USA
| | - Stephan Fischer
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Ricky S Adkins
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Andrew I Aldridge
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Seth A Ament
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - M Margarita Behrens
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Koen Van den Berge
- Department of Statistics, University of California, Berkeley, Berkeley, CA, USA
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Gent, Belgium
| | | | - Hector Roux de Bézieux
- Division of Biostatistics, School of Public Health, University of California, Berkeley, Berkeley, CA, USA
| | | | | | - Héctor Corrada Bravo
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | | | - Carlo Colantuoni
- Johns Hopkins School of Medicine, Department of Neurology, Baltimore, MD, USA
- Johns Hopkins School of Medicine, Department of Neuroscience, Baltimore, MD, USA
- University of Maryland School of Medicine, Institute for Genome Sciences, Baltimore, MD, USA
| | - Jonathan Crabtree
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Heather Creasy
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Megan Crow
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Nick Dee
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Wayne I Doyle
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
| | - Sandrine Dudoit
- Department of Statistics, University of California, Berkeley, Berkeley, CA, USA
| | - Rongxin Fang
- Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, San Diego, CA, USA
| | - Victor Felix
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Olivia Fong
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Michelle Giglio
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jeff Goldy
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Brian R Herb
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Ronna Hertzano
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
- Department of Otorhinolaryngology, Anatomy and Neurobiology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Xiaomeng Hou
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Qiwen Hu
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Jayaram Kancherla
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, College Park, MD, USA
| | | | - Kanan Lathia
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Yang Eric Li
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Jacinta D Lucero
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Chongyuan Luo
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Anup Mahurkar
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Naeem M Nadaf
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Joseph R Nery
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | - Sheng-Yong Niu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Vasilis Ntranos
- University of California, San Francisco, San Francisco, CA, USA
| | - Joshua Orvis
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Julia K Osteen
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Thanh Pham
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Antonio Pinto-Duarte
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Olivier Poirion
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Elizabeth Purdom
- Department of Statistics, University of California, Berkeley, Berkeley, CA, USA
| | | | - Davide Risso
- Department of Statistical Sciences, University of Padova, Padova, Italy
| | - Angeline C Rivkin
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | | | - Kelly Street
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA
| | - Josef Sulc
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Michael Tieu
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Herman Tung
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Xinxin Wang
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO, USA
| | - Owen R White
- Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Z Josh Huang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Peter V Kharchenko
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Lior Pachter
- California Institute of Technology, Pasadena, CA, USA
| | - John Ngai
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Aviv Regev
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Howard Hughes Medical Institute, Department of Biology, MIT, Cambridge, MA, USA
| | | | - Joshua D Welch
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Jesse Gillis
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | | | - Bing Ren
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA.
| | - Eran A Mukamel
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA.
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10
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Callaway EM, Dong HW, Ecker JR, Hawrylycz MJ, Huang ZJ, Lein ES, Ngai J, Osten P, Ren B, Tolias AS, White O, Zeng H, Zhuang X, Ascoli GA, Behrens MM, Chun J, Feng G, Gee JC, Ghosh SS, Halchenko YO, Hertzano R, Lim BK, Martone ME, Ng L, Pachter L, Ropelewski AJ, Tickle TL, Yang XW, Zhang K, Bakken TE, Berens P, Daigle TL, Harris JA, Jorstad NL, Kalmbach BE, Kobak D, Li YE, Liu H, Matho KS, Mukamel EA, Naeemi M, Scala F, Tan P, Ting JT, Xie F, Zhang M, Zhang Z, Zhou J, Zingg B, Armand E, Yao Z, Bertagnolli D, Casper T, Crichton K, Dee N, Diep D, Ding SL, Dong W, Dougherty EL, Fong O, Goldman M, Goldy J, Hodge RD, Hu L, Keene CD, Krienen FM, Kroll M, Lake BB, Lathia K, Linnarsson S, Liu CS, Macosko EZ, McCarroll SA, McMillen D, Nadaf NM, Nguyen TN, Palmer CR, Pham T, Plongthongkum N, Reed NM, Regev A, Rimorin C, Romanow WJ, Savoia S, Siletti K, Smith K, Sulc J, Tasic B, Tieu M, Torkelson A, Tung H, van Velthoven CTJ, Vanderburg CR, Yanny AM, Fang R, Hou X, Lucero JD, Osteen JK, Pinto-Duarte A, Poirion O, Preissl S, Wang X, Aldridge AI, Bartlett A, Boggeman L, O’Connor C, Castanon RG, Chen H, Fitzpatrick C, Luo C, Nery JR, Nunn M, Rivkin AC, Tian W, Dominguez B, Ito-Cole T, Jacobs M, Jin X, Lee CT, Lee KF, Miyazaki PA, Pang Y, Rashid M, Smith JB, Vu M, Williams E, Biancalani T, Booeshaghi AS, Crow M, Dudoit S, Fischer S, Gillis J, Hu Q, Kharchenko PV, Niu SY, Ntranos V, Purdom E, Risso D, de Bézieux HR, Somasundaram S, Street K, Svensson V, Vaishnav ED, Van den Berge K, Welch JD, An X, Bateup HS, Bowman I, Chance RK, Foster NN, Galbavy W, Gong H, Gou L, Hatfield JT, Hintiryan H, Hirokawa KE, Kim G, Kramer DJ, Li A, Li X, Luo Q, Muñoz-Castañeda R, Stafford DA, Feng Z, Jia X, Jiang S, Jiang T, Kuang X, Larsen R, Lesnar P, Li Y, Li Y, Liu L, Peng H, Qu L, Ren M, Ruan Z, Shen E, Song Y, Wakeman W, Wang P, Wang Y, Wang Y, Yin L, Yuan J, Zhao S, Zhao X, Narasimhan A, Palaniswamy R, Banerjee S, Ding L, Huilgol D, Huo B, Kuo HC, Laturnus S, Li X, Mitra PP, Mizrachi J, Wang Q, Xie P, Xiong F, Yu Y, Eichhorn SW, Berg J, Bernabucci M, Bernaerts Y, Cadwell CR, Castro JR, Dalley R, Hartmanis L, Horwitz GD, Jiang X, Ko AL, Miranda E, Mulherkar S, Nicovich PR, Owen SF, Sandberg R, Sorensen SA, Tan ZH, Allen S, Hockemeyer D, Lee AY, Veldman MB, Adkins RS, Ament SA, Bravo HC, Carter R, Chatterjee A, Colantuoni C, Crabtree J, Creasy H, Felix V, Giglio M, Herb BR, Kancherla J, Mahurkar A, McCracken C, Nickel L, Olley D, Orvis J, Schor M, Hood G, Dichter B, Grauer M, Helba B, Bandrowski A, Barkas N, Carlin B, D’Orazi FD, Degatano K, Gillespie TH, Khajouei F, Konwar K, Thompson C, Kelly K, Mok S, Sunkin S. A multimodal cell census and atlas of the mammalian primary motor cortex. Nature 2021; 598:86-102. [PMID: 34616075 PMCID: PMC8494634 DOI: 10.1038/s41586-021-03950-0] [Citation(s) in RCA: 205] [Impact Index Per Article: 68.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Accepted: 08/25/2021] [Indexed: 12/14/2022]
Abstract
Here 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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11
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Kramer DJ, Aisenberg EE, Kosillo P, Friedmann D, Stafford DA, Lee AYF, Luo L, Hockemeyer D, Ngai J, Bateup HS. Generation of a DAT-P2A-Flpo mouse line for intersectional genetic targeting of dopamine neuron subpopulations. Cell Rep 2021; 35:109123. [PMID: 33979604 PMCID: PMC8240967 DOI: 10.1016/j.celrep.2021.109123] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2020] [Revised: 02/10/2021] [Accepted: 04/22/2021] [Indexed: 02/06/2023] Open
Abstract
Dopaminergic projections exert widespread influence over multiple brain regions and modulate various behaviors including movement, reward learning, and motivation. It is increasingly appreciated that dopamine neurons are heterogeneous in their gene expression, circuitry, physiology, and function. Current approaches to target dopamine neurons are largely based on single gene drivers, which either label all dopamine neurons or mark a subset but concurrently label non-dopaminergic neurons. Here, we establish a mouse line with Flpo recombinase expressed from the endogenous Slc6a3 (dopamine active transporter [DAT]) locus. DAT-P2A-Flpo mice can be used together with Cre-expressing mouse lines to efficiently and selectively label dopaminergic subpopulations using Cre/Flp-dependent intersectional strategies. We demonstrate the utility of this approach by generating DAT-P2A-Flpo;NEX-Cre mice that specifically label Neurod6-expressing dopamine neurons, which project to the nucleus accumbens medial shell. DAT-P2A-Flpo mice add to a growing toolbox of genetic resources that will help parse the diverse functions mediated by dopaminergic circuits. Kramer et al. generate a DAT-P2A-Flpo mouse line that enables intersectional genetic targeting of dopamine neuron subpopulations using Flp/Cre-dependent constructs. They show that ventral tegmental area dopamine neurons expressing Neurod6 give rise to the majority of dopaminergic projections to the nucleus accumbens medial shell and olfactory tubercle.
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Affiliation(s)
- Daniel J Kramer
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Erin E Aisenberg
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Polina Kosillo
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Drew Friedmann
- Howard Hughes Medical Institute and Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - David A Stafford
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Angus Yiu-Fai Lee
- Cancer Research Laboratory, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Liqun Luo
- Howard Hughes Medical Institute and Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Dirk Hockemeyer
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA; Innovative Genomics Institute, University of California, Berkeley, CA 94720, USA
| | - John Ngai
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Helen S Bateup
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA.
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12
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Hsu NS, Fang HY, David KK, Gnadt JW, Peng GC, Talley EM, Ward JM, Ngai J, Koroshetz WJ. The promise of the BRAIN initiative: NIH strategies for understanding neural circuit function. Curr Opin Neurobiol 2020; 65:162-166. [PMID: 33279793 DOI: 10.1016/j.conb.2020.10.008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 10/09/2020] [Accepted: 10/11/2020] [Indexed: 10/22/2022]
Abstract
New neurotechnologies fueled by the BRAIN Initiative now allow investigators to map, monitor and modulate complex neural circuits, enabling the pursuit of research questions previously considered unapproachable. Yet it is the convergence of molecular neuroscience with the new systems neuroscience that promises the greatest future advances. This is particularly true for our understanding of nervous system disorders, some of which have known molecular drivers or pathology but result in unknown perturbations in circuit function. NIH-supported research on "BRAIN Circuits" programs integrate experimental, analytic, and theoretical capabilities for analysis of specific neural circuits and their contributions to perceptions, motivations, and actions. In this review, we describe the BRAIN priority areas, review our strategy for balancing early feasibility with mature projects, and the balance of individual with team science for this 'BRAIN Circuits' program. We also highlight the diverse portfolio of techniques, species, and neural systems represented in these projects.
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13
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Pool AH, Wang T, Stafford DA, Chance RK, Lee S, Ngai J, Oka Y. The cellular basis of distinct thirst modalities. Nature 2020; 588:112-117. [PMID: 33057193 PMCID: PMC7718410 DOI: 10.1038/s41586-020-2821-8] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Accepted: 07/16/2020] [Indexed: 12/16/2022]
Abstract
Fluid intake is an essential innate behavior mainly caused by two distinct types of thirst1–3. Increased blood osmolality induces osmotic thirst that drives animals to consume pure water. Conversely, the loss of body fluid induces hypovolemic thirst in which animals seek both water and minerals (salts) to recover blood volume. Circumventricular organs (CVOs) in the lamina terminalis (LT) are critical sites for sensing both types of thirst-inducing stimuli4–6. However, how different thirst modalities are encoded in the brain remains unknown. Here, we employed stimulus to cell-type mapping using single-cell RNA-seq (scRNA-seq) to determine the cellular substrate underlying distinct types of thirst. These studies revealed diverse excitatory and inhibitory neuron types in each CVO structure. Among them, we show that unique combinations of neuron types are activated under osmotic and hypovolemic stresses. These results elucidate the cellular logic underlying distinct thirst modalities. Furthermore, optogenetic gain-of-function in thirst-modality-specific cell types recapitulated water-specific and non-specific fluid appetite caused by the two distinct dipsogenic stimuli. Taken together, this study demonstrates that thirst is a multimodal physiological state, and that different thirst states are mediated by specific neuron types in the mammalian brain.
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Affiliation(s)
- Allan-Hermann Pool
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Tongtong Wang
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.,College of Life Sciences, Nankai University, Tianjin, China
| | - David A Stafford
- Department of Molecular & Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Rebecca K Chance
- Department of Molecular & Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Sangjun Lee
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - John Ngai
- Department of Molecular & Cell Biology, University of California, Berkeley, Berkeley, CA, USA.,National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - Yuki Oka
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
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14
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Brann DH, Tsukahara T, Weinreb C, Lipovsek M, Van den Berge K, Gong B, Chance R, Macaulay IC, Chou HJ, Fletcher RB, Das D, Street K, de Bezieux HR, Choi YG, Risso D, Dudoit S, Purdom E, Mill J, Hachem RA, Matsunami H, Logan DW, Goldstein BJ, Grubb MS, Ngai J, Datta SR. Non-neuronal expression of SARS-CoV-2 entry genes in the olfactory system suggests mechanisms underlying COVID-19-associated anosmia. Sci Adv 2020; 6:eabc5801. [PMID: 32937591 PMCID: PMC10715684 DOI: 10.1126/sciadv.abc5801] [Citation(s) in RCA: 666] [Impact Index Per Article: 166.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2020] [Accepted: 06/18/2020] [Indexed: 05/05/2023]
Abstract
Altered olfactory function is a common symptom of COVID-19, but its etiology is unknown. A key question is whether SARS-CoV-2 (CoV-2) - the causal agent in COVID-19 - affects olfaction directly, by infecting olfactory sensory neurons or their targets in the olfactory bulb, or indirectly, through perturbation of supporting cells. Here we identify cell types in the olfactory epithelium and olfactory bulb that express SARS-CoV-2 cell entry molecules. Bulk sequencing demonstrated that mouse, non-human primate and human olfactory mucosa expresses two key genes involved in CoV-2 entry, ACE2 and TMPRSS2. However, single cell sequencing revealed that ACE2 is expressed in support cells, stem cells, and perivascular cells, rather than in neurons. Immunostaining confirmed these results and revealed pervasive expression of ACE2 protein in dorsally-located olfactory epithelial sustentacular cells and olfactory bulb pericytes in the mouse. These findings suggest that CoV-2 infection of non-neuronal cell types leads to anosmia and related disturbances in odor perception in COVID-19 patients.
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Affiliation(s)
- David H Brann
- Harvard Medical School Department of Neurobiology, Boston MA 02115 USA
| | - Tatsuya Tsukahara
- Harvard Medical School Department of Neurobiology, Boston MA 02115 USA
| | - Caleb Weinreb
- Harvard Medical School Department of Neurobiology, Boston MA 02115 USA
| | - Marcela Lipovsek
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London SE1 1UL, UK
| | - Koen Van den Berge
- Department of Statistics, University of California, Berkeley, CA 94720
- Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium
| | - Boying Gong
- Division of Biostatistics, School of Public Health, University of California, Berkeley, CA 94720
| | - Rebecca Chance
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720
| | - Iain C Macaulay
- Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, UK
| | - Hsin-Jung Chou
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720
| | - Russell B Fletcher
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720
- Present address: Surrozen, Inc., South San Francisco, CA 94080
| | - Diya Das
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720
- Berkeley Institute for Data Science, University of California, Berkeley
- Present address: Genentech, Inc., South San Francisco, CA 94080
| | - Kelly Street
- Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Hector Roux de Bezieux
- Division of Biostatistics, School of Public Health, University of California, Berkeley, CA 94720
- Center for Computational Biology, University of California, Berkeley, CA 94720
| | - Yoon-Gi Choi
- QB3 Functional Genomics Laboratory, University of California, Berkeley, CA 94720
| | - Davide Risso
- Department of Statistical Sciences, University of Padova, Padova, Italy
| | - Sandrine Dudoit
- Department of Statistics, University of California, Berkeley, CA 94720
- Division of Biostatistics, School of Public Health, University of California, Berkeley, CA 94720
| | - Elizabeth Purdom
- Department of Statistics, University of California, Berkeley, CA 94720
| | - Jonathan Mill
- University of Exeter Medical School, College of Medicine & Health, University of Exeter, Exeter EX2 5DW, UK
| | - Ralph Abi Hachem
- Duke University School of Medicine Department of Head and Neck Surgery & Communication Sciences, Durham, NC 27717 USA
| | - Hiroaki Matsunami
- Duke University School of Medicine Department of Molecular Genetics and Microbiology, Department of Neurobiology, Duke Institute for Brain Sciences, Durham, NC 27717 US
| | - Darren W Logan
- Waltham Petcare Science Institute, Leicestershire LE14 4RT, UK
| | - Bradley J Goldstein
- Duke University School of Medicine Department of Head and Neck Surgery & Communication Sciences, Durham, NC 27717 USA
| | - Matthew S Grubb
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London SE1 1UL, UK
| | - John Ngai
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720
- QB3 Functional Genomics Laboratory, University of California, Berkeley, CA 94720
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720
- Present address: National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD
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15
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Cole MB, Risso D, Wagner A, DeTomaso D, Ngai J, Purdom E, Dudoit S, Yosef N. Performance Assessment and Selection of Normalization Procedures for Single-Cell RNA-Seq. Cell Syst 2020; 8:315-328.e8. [PMID: 31022373 DOI: 10.1016/j.cels.2019.03.010] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Revised: 02/07/2019] [Accepted: 03/15/2019] [Indexed: 01/17/2023]
Abstract
Systematic measurement biases make normalization an essential step in single-cell RNA sequencing (scRNA-seq) analysis. There may be multiple competing considerations behind the assessment of normalization performance, of which some may be study specific. We have developed "scone"- a flexible framework for assessing performance based on a comprehensive panel of data-driven metrics. Through graphical summaries and quantitative reports, scone summarizes trade-offs and ranks large numbers of normalization methods by panel performance. The method is implemented in the open-source Bioconductor R software package scone. We show that top-performing normalization methods lead to better agreement with independent validation data for a collection of scRNA-seq datasets. scone can be downloaded at http://bioconductor.org/packages/scone/.
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Affiliation(s)
- Michael B Cole
- Department of Physics, University of California, Berkeley, CA, USA.
| | - Davide Risso
- Department of Statistical Sciences, University of Padova, Padova, Italy; Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, NY, USA.
| | - Allon Wagner
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA; Center for Computational Biology, University of California, Berkeley, CA, USA
| | - David DeTomaso
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - John Ngai
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
| | - Elizabeth Purdom
- Center for Computational Biology, University of California, Berkeley, CA, USA; Department of Statistics, University of California, Berkeley, CA, USA
| | - Sandrine Dudoit
- Center for Computational Biology, University of California, Berkeley, CA, USA; Department of Statistics, University of California, Berkeley, CA, USA; Division of Epidemiology and Biostatistics, School of Public Health, University of California, Berkeley, CA, USA
| | - Nir Yosef
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA; Center for Computational Biology, University of California, Berkeley, CA, USA.
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16
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Covello G, Rossello FJ, Filosi M, Gajardo F, Duchemin A, Tremonti BF, Eichenlaub M, Polo JM, Powell D, Ngai J, Allende ML, Domenici E, Ramialison M, Poggi L. Transcriptome analysis of the zebrafish atoh7-/- Mutant, lakritz, highlights Atoh7-dependent genetic networks with potential implications for human eye diseases. FASEB Bioadv 2020; 2:434-448. [PMID: 32676583 PMCID: PMC7354691 DOI: 10.1096/fba.2020-00030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 04/02/2020] [Accepted: 04/28/2020] [Indexed: 12/21/2022] Open
Abstract
Expression of the bHLH transcription protein Atoh7 is a crucial factor conferring competence to retinal progenitor cells for the development of retinal ganglion cells. Several studies have emerged establishing ATOH7 as a retinal disease gene. Remarkably, such studies uncovered ATOH7 variants associated with global eye defects including optic nerve hypoplasia, microphthalmia, retinal vascular disorders, and glaucoma. The complex genetic networks and cellular decisions arising downstream of atoh7 expression, and how their dysregulation cause development of such disease traits remains unknown. To begin to understand such Atoh7-dependent events in vivo, we performed transcriptome analysis of wild-type and atoh7 mutant (lakritz) zebrafish embryos at the onset of retinal ganglion cell differentiation. We investigated in silico interplays of atoh7 and other disease-related genes and pathways. By network reconstruction analysis of differentially expressed genes, we identified gene clusters enriched in retinal development, cell cycle, chromatin remodeling, stress response, and Wnt pathways. By weighted gene coexpression network, we identified coexpression modules affected by the mutation and enriched in retina development genes tightly connected to atoh7. We established the groundwork whereby Atoh7-linked cellular and molecular processes can be investigated in the dynamic multi-tissue environment of the developing normal and diseased vertebrate eye.
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Affiliation(s)
- Giuseppina Covello
- Department of Cellular, Computational and Integrative Biology ‐ CIBIOUniversity of TrentoTrentoItaly
- Present address:
Department of BiologyUniversity of PadovaPadovaItaly
| | - Fernando J. Rossello
- Australian Regenerative Medicine InstituteMonash University Clayton VICClaytonAustralia
- Present address:
University of Melbourne Centre for Cancer ResearchUniversity of MelbourneMelbourneVictoriaAustralia
| | - Michele Filosi
- Department of Cellular, Computational and Integrative Biology ‐ CIBIOUniversity of TrentoTrentoItaly
| | - Felipe Gajardo
- Center for Genome RegulationFacultad de Ciencias, SantiagoUniversidad de ChileSantiagoChile
| | | | - Beatrice F. Tremonti
- Department of Cellular, Computational and Integrative Biology ‐ CIBIOUniversity of TrentoTrentoItaly
| | - Michael Eichenlaub
- Australian Regenerative Medicine InstituteMonash University Clayton VICClaytonAustralia
| | - Jose M. Polo
- Australian Regenerative Medicine InstituteMonash University Clayton VICClaytonAustralia
- BDIMonash University Clayton VICClaytonAustralia
| | - David Powell
- Monash Bioinformatics PlatformMonash University Clayton VICClaytonAustralia
| | - John Ngai
- Department of Molecular and Cell Biology & Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCAUSA
| | - Miguel L. Allende
- Center for Genome RegulationFacultad de Ciencias, SantiagoUniversidad de ChileSantiagoChile
| | - Enrico Domenici
- Department of Cellular, Computational and Integrative Biology ‐ CIBIOUniversity of TrentoTrentoItaly
- Fondazione The Microsoft Research ‐ University of Trento Centre for Computational and Systems BiologyTrentoItaly
| | - Mirana Ramialison
- Australian Regenerative Medicine InstituteMonash University Clayton VICClaytonAustralia
| | - Lucia Poggi
- Department of Cellular, Computational and Integrative Biology ‐ CIBIOUniversity of TrentoTrentoItaly
- Centre for Organismal StudyHeidelberg UniversityHeidelbergGermany
- Department of PhysiologyDevelopment and NeuroscienceUniversity of CambridgeCambridgeUnited Kingdom
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17
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Das D, Fletcher RB, Ngai J. Cellular mechanisms of epithelial stem cell self-renewal and differentiation during homeostasis and repair. Wiley Interdiscip Rev Dev Biol 2019; 9:e361. [PMID: 31468728 DOI: 10.1002/wdev.361] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Revised: 07/31/2019] [Accepted: 08/02/2019] [Indexed: 12/14/2022]
Abstract
Epithelia in adult mammals exhibit remarkable regenerative capacities owing to the presence of adult stem cells, which self-renew and differentiate to replace cells lost to normal turnover or injury. The mechanisms supporting tissue homeostasis and injury-induced repair often differ from each other as well as from those used in embryonic development. Recent studies have also highlighted the phenomenon of cellular plasticity in adult tissues, in which differentiated cells can change fate and even give rise to new stem cell populations to complement the canonical stem cells in promoting repair following injury. Signaling pathways such as WNT, bone morphogenetic protein, and Sonic Hedgehog play critical roles in stem cell maintenance and cell fate decisions across diverse epithelia and conditions, suggesting that conserved mechanisms underlie the regenerative capacity of adult epithelial structures. This article is categorized under: Gene Expression and Transcriptional Hierarchies > Regulatory Mechanisms Adult Stem Cells, Tissue Renewal, and Regeneration > Tissue Stem Cells and Niches Adult Stem Cells, Tissue Renewal, and Regeneration > Stem Cell Differentiation and Reversion Adult Stem Cells, Tissue Renewal, and Regeneration > Regeneration.
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Affiliation(s)
- Diya Das
- Department of Molecular and Cell Biology, University of California, Berkeley, California.,Berkeley Institute for Data Science, University of California, Berkeley, California
| | - Russell B Fletcher
- Department of Molecular and Cell Biology, University of California, Berkeley, California
| | - John Ngai
- Department of Molecular and Cell Biology, University of California, Berkeley, California.,Helen Wills Neuroscience Institute, University of California, Berkeley, California.,QB3 Functional Genomics Laboratory, University of California, Berkeley, California
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18
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Abstract
The diversity of brain cell types was one of the earliest observations in modern neuroscience and continues to be one of the central concerns of current neuroscience research. Despite impressive recent progress, including single cell transcriptome and epigenome profiling as well as anatomical methods, we still lack a complete census or taxonomy of brain cell types. We argue this is due partly to the conceptual difficulty in defining a cell type. By considering the biological drivers of cell identity, such as networks of genes and gene regulatory elements, we propose a definition of cell type that emphasizes self-stabilizing regulation. We explore the predictions and hypotheses that arise from this definition. Integration of data from multiple modalities, including molecular profiling of genes and gene products, epigenetic landscape, cellular morphology, connectivity, and physiology, will be essential for a meaningful and broadly useful definition of brain cell types.
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Affiliation(s)
- Eran A Mukamel
- Department of Cognitive Science, University of California, San Diego, CA 92037, United States.
| | - John Ngai
- Department of Molecular and Cell Biology, Helen Wills Neuroscience Institute, QB3 Functional Genomics Laboratory, University of California, Berkeley, CA 94720, United States.
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19
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Naka A, Veit J, Shababo B, Chance RK, Risso D, Stafford D, Snyder B, Egladyous A, Chu D, Sridharan S, Mossing DP, Paninski L, Ngai J, Adesnik H. Complementary networks of cortical somatostatin interneurons enforce layer specific control. eLife 2019; 8:43696. [PMID: 30883329 PMCID: PMC6422636 DOI: 10.7554/elife.43696] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2018] [Accepted: 02/08/2019] [Indexed: 12/03/2022] Open
Abstract
The neocortex is functionally organized into layers. Layer four receives the densest bottom up sensory inputs, while layers 2/3 and 5 receive top down inputs that may convey predictive information. A subset of cortical somatostatin (SST) neurons, the Martinotti cells, gate top down input by inhibiting the apical dendrites of pyramidal cells in layers 2/3 and 5, but it is unknown whether an analogous inhibitory mechanism controls activity in layer 4. Using high precision circuit mapping, in vivo optogenetic perturbations, and single cell transcriptional profiling, we reveal complementary circuits in the mouse barrel cortex involving genetically distinct SST subtypes that specifically and reciprocally interconnect with excitatory cells in different layers: Martinotti cells connect with layers 2/3 and 5, whereas non-Martinotti cells connect with layer 4. By enforcing layer-specific inhibition, these parallel SST subnetworks could independently regulate the balance between bottom up and top down input.
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Affiliation(s)
- Alexander Naka
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
| | - Julia Veit
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
| | - Ben Shababo
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States
| | - Rebecca K Chance
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
| | - Davide Risso
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States.,Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States.,Department of Statistical Sciences, University of Padova, Padova, Italy.,Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, United States
| | - David Stafford
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
| | - Benjamin Snyder
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
| | - Andrew Egladyous
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
| | - Desiree Chu
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
| | - Savitha Sridharan
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
| | - Daniel P Mossing
- Department of Biophysics, University of California, Berkeley, Berkeley, United States
| | - Liam Paninski
- Neurobiology and Behavior Program, Columbia University, New York, United States.,Center for Theoretical Neuroscience, Columbia University, New York, United States.,Departments of Statistics and Neuroscience, Columbia University, New York, United States.,Grossman Center for the Statistics of Mind, Columbia University, New York, United States
| | - John Ngai
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States.,Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States.,QB3 Functional Genomics Laboratory, University of California, Berkeley, Berkeley, United States
| | - Hillel Adesnik
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, United States.,Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
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20
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Risso D, Purvis L, Fletcher RB, Das D, Ngai J, Dudoit S, Purdom E. clusterExperiment and RSEC: A Bioconductor package and framework for clustering of single-cell and other large gene expression datasets. PLoS Comput Biol 2018; 14:e1006378. [PMID: 30180157 PMCID: PMC6138422 DOI: 10.1371/journal.pcbi.1006378] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Revised: 09/14/2018] [Accepted: 07/18/2018] [Indexed: 12/02/2022] Open
Abstract
Clustering of genes and/or samples is a common task in gene expression analysis. The goals in clustering can vary, but an important scenario is that of finding biologically meaningful subtypes within the samples. This is an application that is particularly appropriate when there are large numbers of samples, as in many human disease studies. With the increasing popularity of single-cell transcriptome sequencing (RNA-Seq), many more controlled experiments on model organisms are similarly creating large gene expression datasets with the goal of detecting previously unknown heterogeneity within cells. It is common in the detection of novel subtypes to run many clustering algorithms, as well as rely on subsampling and ensemble methods to improve robustness. We introduce a Bioconductor R package, clusterExperiment, that implements a general and flexible strategy we entitle Resampling-based Sequential Ensemble Clustering (RSEC). RSEC enables the user to easily create multiple, competing clusterings of the data based on different techniques and associated tuning parameters, including easy integration of resampling and sequential clustering, and then provides methods for consolidating the multiple clusterings into a final consensus clustering. The package is modular and allows the user to separately apply the individual components of the RSEC procedure, i.e., apply multiple clustering algorithms, create a consensus clustering or choose tuning parameters, and merge clusters. Additionally, clusterExperiment provides a variety of visualization tools for the clustering process, as well as methods for the identification of possible cluster signatures or biomarkers. The R package clusterExperiment is publicly available through the Bioconductor Project, with a detailed manual (vignette) as well as well documented help pages for each function.
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Affiliation(s)
- Davide Risso
- Division of Biostatistics and Epidemiology, Weill Cornell Medicine, New York, New York, United States of America
| | - Liam Purvis
- Department of Statistics, University of California - Berkeley, Berkeley, California, United States of America
| | - Russell B. Fletcher
- Department of Molecular and Cell Biology, University of California - Berkeley, Berkeley, California, United States of America
| | - Diya Das
- Department of Molecular and Cell Biology, University of California - Berkeley, Berkeley, California, United States of America
- Berkeley Institute for Data Science, UC University of California - Berkeley, Berkeley, California, United States of America
| | - John Ngai
- Department of Molecular and Cell Biology, University of California - Berkeley, Berkeley, California, United States of America
| | - Sandrine Dudoit
- Department of Statistics, University of California - Berkeley, Berkeley, California, United States of America
- Berkeley Institute for Data Science, UC University of California - Berkeley, Berkeley, California, United States of America
- Division of Epidemiology and Biostatistics, University of California - Berkeley, Berkeley, California, United States of America
| | - Elizabeth Purdom
- Department of Statistics, University of California - Berkeley, Berkeley, California, United States of America
- * E-mail:
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21
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Street K, Risso D, Fletcher RB, Das D, Ngai J, Yosef N, Purdom E, Dudoit S. Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genomics 2018; 19:477. [PMID: 29914354 PMCID: PMC6007078 DOI: 10.1186/s12864-018-4772-0] [Citation(s) in RCA: 1098] [Impact Index Per Article: 183.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Accepted: 05/09/2018] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Single-cell transcriptomics allows researchers to investigate complex communities of heterogeneous cells. It can be applied to stem cells and their descendants in order to chart the progression from multipotent progenitors to fully differentiated cells. While a variety of statistical and computational methods have been proposed for inferring cell lineages, the problem of accurately characterizing multiple branching lineages remains difficult to solve. RESULTS We introduce Slingshot, a novel method for inferring cell lineages and pseudotimes from single-cell gene expression data. In previously published datasets, Slingshot correctly identifies the biological signal for one to three branching trajectories. Additionally, our simulation study shows that Slingshot infers more accurate pseudotimes than other leading methods. CONCLUSIONS Slingshot is a uniquely robust and flexible tool which combines the highly stable techniques necessary for noisy single-cell data with the ability to identify multiple trajectories. Accurate lineage inference is a critical step in the identification of dynamic temporal gene expression.
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Affiliation(s)
- Kelly Street
- Division of Biostatistics, School of Public Health, University of California, Berkeley, CA USA
- Center for Computational Biology, University of California, Berkeley, CA USA
| | - Davide Risso
- Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Cornell Medicine, 407 E 61st St, New York, 10065 NY USA
| | - Russell B. Fletcher
- Department of Molecular and Cell Biology, University of California, Berkeley, CA USA
| | - Diya Das
- Department of Molecular and Cell Biology, University of California, Berkeley, CA USA
- Berkeley Institute for Data Science, University of California, Berkeley, CA USA
| | - John Ngai
- Department of Molecular and Cell Biology, University of California, Berkeley, CA USA
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA USA
- QB3 Berkeley Functional Genomics Laboratory, Berkeley, CA USA
| | - Nir Yosef
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA USA
- Center for Computational Biology, University of California, Berkeley, CA USA
| | - Elizabeth Purdom
- Department of Statistics, University of California, Berkeley, CA USA
- Center for Computational Biology, University of California, Berkeley, CA USA
| | - Sandrine Dudoit
- Division of Biostatistics, School of Public Health, University of California, Berkeley, CA USA
- Department of Statistics, University of California, Berkeley, CA USA
- Center for Computational Biology, University of California, Berkeley, CA USA
- Berkeley Institute for Data Science, University of California, Berkeley, CA USA
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22
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Kramer DJ, Risso D, Kosillo P, Ngai J, Bateup HS. Combinatorial Expression of Grp and Neurod6 Defines Dopamine Neuron Populations with Distinct Projection Patterns and Disease Vulnerability. eNeuro 2018; 5:ENEURO.0152-18.2018. [PMID: 30135866 PMCID: PMC6104179 DOI: 10.1523/eneuro.0152-18.2018] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 05/14/2018] [Indexed: 12/15/2022] Open
Abstract
Midbrain dopamine neurons project to numerous targets throughout the brain to modulate various behaviors and brain states. Within this small population of neurons exists significant heterogeneity based on physiology, circuitry, and disease susceptibility. Recent studies have shown that dopamine neurons can be subdivided based on gene expression; however, the extent to which genetic markers represent functionally relevant dopaminergic subpopulations has not been fully explored. Here we performed single-cell RNA-sequencing of mouse dopamine neurons and validated studies showing that Neurod6 and Grp are selective markers for dopaminergic subpopulations. Using a combination of multiplex fluorescent in situ hybridization, retrograde labeling, and electrophysiology in mice of both sexes, we defined the anatomy, projection targets, physiological properties, and disease vulnerability of dopamine neurons based on Grp and/or Neurod6 expression. We found that the combinatorial expression of Grp and Neurod6 defines dopaminergic subpopulations with unique features. Grp+/Neurod6+ dopamine neurons reside in the ventromedial VTA, send projections to the medial shell of the nucleus accumbens, and have noncanonical physiological properties. Grp+/Neurod6- dopamine neurons are found in the VTA as well as in the ventromedial portion of the SNc, where they project selectively to the dorsomedial striatum. Grp-/Neurod6+ dopamine neurons represent a smaller VTA subpopulation, which is preferentially spared in a 6-OHDA model of Parkinson's disease. Together, our work provides detailed characterization of Neurod6 and Grp expression in the midbrain and generates new insights into how these markers define functionally relevant dopaminergic subpopulations.
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Affiliation(s)
- Daniel J. Kramer
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720
| | - Davide Risso
- Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, NY 10065
| | - Polina Kosillo
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720
| | - John Ngai
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720
| | - Helen S. Bateup
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720
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23
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Gadye L, Das D, Sanchez MA, Street K, Baudhuin A, Wagner A, Cole MB, Choi YG, Yosef N, Purdom E, Dudoit S, Risso D, Ngai J, Fletcher RB. Injury Activates Transient Olfactory Stem Cell States with Diverse Lineage Capacities. Cell Stem Cell 2017; 21:775-790.e9. [PMID: 29174333 DOI: 10.1016/j.stem.2017.10.014] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Revised: 09/20/2017] [Accepted: 10/30/2017] [Indexed: 12/15/2022]
Abstract
Tissue homeostasis and regeneration are mediated by programs of adult stem cell renewal and differentiation. However, the mechanisms that regulate stem cell fates under such widely varying conditions are not fully understood. Using single-cell techniques, we assessed the transcriptional changes associated with stem cell self-renewal and differentiation and followed the maturation of stem cell-derived clones using sparse lineage tracing in the regenerating mouse olfactory epithelium. Following injury, quiescent olfactory stem cells rapidly shift to activated, transient states unique to regeneration and tailored to meet the demands of injury-induced repair, including barrier formation and proliferation. Multiple cell fates, including renewed stem cells and committed differentiating progenitors, are specified during this early window of activation. We further show that Sox2 is essential for cells to transition from the activated to neuronal progenitor states. Our study highlights strategies for stem cell-mediated regeneration that may be conserved in other adult stem cell niches.
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Affiliation(s)
- Levi Gadye
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Diya Das
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Berkeley Institute for Data Science, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Michael A Sanchez
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Kelly Street
- Division of Biostatistics, University of California, Berkeley, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Ariane Baudhuin
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Allon Wagner
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Michael B Cole
- Department of Physics, University of California, Berkeley, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Yoon Gi Choi
- QB3 Functional Genomics Laboratory, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Nir Yosef
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Elizabeth Purdom
- Department of Statistics, University of California, Berkeley, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Sandrine Dudoit
- Berkeley Institute for Data Science, University of California, Berkeley, Berkeley, CA 94720, USA; Division of Biostatistics, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Statistics, University of California, Berkeley, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Davide Risso
- Division of Biostatistics, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Healthcare Policy and Research, Weill Cornell Medical College, New York, NY 10065, USA
| | - John Ngai
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; QB3 Functional Genomics Laboratory, University of California, Berkeley, Berkeley, CA 94720, USA.
| | - Russell B Fletcher
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
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24
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Ecker JR, Geschwind DH, Kriegstein AR, Ngai J, Osten P, Polioudakis D, Regev A, Sestan N, Wickersham IR, Zeng H. The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas. Neuron 2017; 96:542-557. [PMID: 29096072 DOI: 10.1016/j.neuron.2017.10.007] [Citation(s) in RCA: 163] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 10/01/2017] [Accepted: 10/03/2017] [Indexed: 10/25/2022]
Abstract
A comprehensive characterization of neuronal cell types, their distributions, and patterns of connectivity is critical for understanding the properties of neural circuits and how they generate behaviors. Here we review the experiences of the BRAIN Initiative Cell Census Consortium, ten pilot projects funded by the U.S. BRAIN Initiative, in developing, validating, and scaling up emerging genomic and anatomical mapping technologies for creating a complete inventory of neuronal cell types and their connections in multiple species and during development. These projects lay the foundation for a larger and longer-term effort to generate whole-brain cell atlases in species including mice and humans.
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Affiliation(s)
- Joseph R Ecker
- Genomic Analysis Laboratory and Howard Hughes Medical Institute, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Daniel H Geschwind
- Program in Neurogenetics, Departments of Neurology and Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Arnold R Kriegstein
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, Department of Neurology, University of California, San Francisco, San Francisco, CA 94143, USA
| | - John Ngai
- Department of Molecular and Cell Biology, Helen Wills Neuroscience Institute, QB3 Functional Genomics Laboratory, University of California, Berkeley, Berkeley, CA 94720, USA.
| | - Pavel Osten
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Damon Polioudakis
- Program in Neurogenetics, Departments of Neurology and Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Department of Biology, Koch Institute of Integrative Cancer Research, and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Nenad Sestan
- Departments of Neuroscience, Genetics, Psychiatry and Comparative Medicine, Program in Cellular Neuroscience, Neurodegeneration and Repair, Yale Child Study Center, Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Ian R Wickersham
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA 98109, USA
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25
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Abstract
Anosmia and hyposmia, the inability or decreased ability to smell, is estimated to afflict 3-20% of the population. Risk of olfactory dysfunction increases with old age and may also result from chronic sinonasal diseases, severe head trauma, and upper respiratory infections, or neurodegenerative diseases. These disorders impair the ability to sense warning odors in foods and the environment, as well as hinder the quality of life related to social interactions, eating, and feelings of well-being. This article reports and extends on a clinical update commencing at the 2016 Association for Chemoreception Sciences annual meeting. Included were reports from: a patient perspective on losing the sense of smell with information on Fifth Sense, a nonprofit advocacy organization for patients with olfactory disorders; an otolaryngologist's review of clinical evaluation, diagnosis, and management/treatment of anosmia; and researchers' review of recent advances in potential anosmia treatments from fundamental science, in animal, cellular, or genetic models. As limited evidence-based treatments exist for anosmia, dissemination of information on anosmia-related health risks is needed. This could include feasible and useful screening measures for olfactory dysfunction, appropriate clinical evaluation, and patient counseling to avoid harm as well as manage health and quality of life with anosmia.
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Affiliation(s)
- Sanne Boesveldt
- Division of Human Nutrition, Wageningen University & Research, Wageningen, The Netherlands
| | - Elbrich M Postma
- Division of Human Nutrition, Wageningen University & Research, Wageningen, The Netherlands
- Smell and Taste Centre, Hospital Gelderse Vallei, PO Box 9025, 6710 HN Ede, The Netherlands
| | - Duncan Boak
- Fifth Sense, Sanderum House, 38 Oakley Road, Chino OX39 4TW, UK
| | - Antje Welge-Luessen
- Department of Otorhinolaryngology, University Hospital Basel, Petersgraben 4CH-4031 Basel, Switzerland
| | - Veronika Schöpf
- Institute of Psychology, University of Graz, Universitätsplatz 2, 8010 Graz, Austria
- BioTechMed Graz, Mozartgasse 12/II, 8010 Graz, Austria
| | - Joel D Mainland
- Monell Chemical Senses Center, 3500 Market Street, Philadelphia, PA 19104, USA
- Department of Neuroscience, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Jeffrey Martens
- Department of Pharmacology & Therapeutics, University of Florida, Gainesville, FL, USA
| | - John Ngai
- Department of Molecular & Cell Biology, University of California, Berkeley, CA 94720-3200, USA
| | - Valerie B Duffy
- Department of Allied Health Sciences, University of Connecticut, 358 Mansfield Road, Box U-101 Storrs, CT 06269-2101, USA
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Fletcher RB, Das D, Gadye L, Street KN, Baudhuin A, Wagner A, Cole MB, Flores Q, Choi YG, Yosef N, Purdom E, Dudoit S, Risso D, Ngai J. Deconstructing Olfactory Stem Cell Trajectories at Single-Cell Resolution. Cell Stem Cell 2017; 20:817-830.e8. [PMID: 28506465 DOI: 10.1016/j.stem.2017.04.003] [Citation(s) in RCA: 123] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Revised: 03/02/2017] [Accepted: 04/10/2017] [Indexed: 01/08/2023]
Abstract
A detailed understanding of the paths that stem cells traverse to generate mature progeny is vital for elucidating the mechanisms governing cell fate decisions and tissue homeostasis. Adult stem cells maintain and regenerate multiple mature cell lineages in the olfactory epithelium. Here we integrate single-cell RNA sequencing and robust statistical analyses with in vivo lineage tracing to define a detailed map of the postnatal olfactory epithelium, revealing cell fate potentials and branchpoints in olfactory stem cell lineage trajectories. Olfactory stem cells produce support cells via direct fate conversion in the absence of cell division, and their multipotency at the population level reflects collective unipotent cell fate decisions by single stem cells. We further demonstrate that Wnt signaling regulates stem cell fate by promoting neuronal fate choices. This integrated approach reveals the mechanisms guiding olfactory lineage trajectories and provides a model for deconstructing similar hierarchies in other stem cell niches.
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Affiliation(s)
- Russell B Fletcher
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
| | - Diya Das
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
| | - Levi Gadye
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA
| | - Kelly N Street
- Division of Biostatistics, University of California, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, CA 94720, USA
| | - Ariane Baudhuin
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
| | - Allon Wagner
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, CA 94720, USA
| | - Michael B Cole
- Department of Physics, University of California, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, CA 94720, USA
| | - Quetzal Flores
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
| | - Yoon Gi Choi
- QB3 Functional Genomics Laboratory, University of California, Berkeley, CA 94720, USA
| | - Nir Yosef
- Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, CA 94720, USA
| | - Elizabeth Purdom
- Department of Statistics, University of California, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, CA 94720, USA
| | - Sandrine Dudoit
- Division of Biostatistics, University of California, Berkeley, CA 94720, USA; Department of Statistics, University of California, Berkeley, CA 94720, USA; Center for Computational Biology, University of California, Berkeley, CA 94720, USA
| | - Davide Risso
- Division of Biostatistics, University of California, Berkeley, CA 94720, USA
| | - John Ngai
- Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA; QB3 Functional Genomics Laboratory, University of California, Berkeley, CA 94720, USA.
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27
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Ferreira T, Wilson SR, Choi YG, Risso D, Dudoit S, Speed TP, Ngai J. Silencing of odorant receptor genes by G protein βγ signaling ensures the expression of one odorant receptor per olfactory sensory neuron. Neuron 2014; 81:847-59. [PMID: 24559675 DOI: 10.1016/j.neuron.2014.01.001] [Citation(s) in RCA: 42] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/12/2013] [Indexed: 02/06/2023]
Abstract
Olfactory sensory neurons express just one out of a possible ∼ 1,000 odorant receptor genes, reflecting an exquisite mode of gene regulation. In one model, once an odorant receptor is chosen for expression, other receptor genes are suppressed by a negative feedback mechanism, ensuring a stable functional identity of the sensory neuron for the lifetime of the cell. The signal transduction mechanism subserving odorant receptor gene silencing remains obscure, however. Here, we demonstrate in the zebrafish that odorant receptor gene silencing is dependent on receptor activity. Moreover, we show that signaling through G protein βγ subunits is both necessary and sufficient to suppress the expression of odorant receptor genes and likely acts through histone methylation to maintain the silenced odorant receptor genes in transcriptionally inactive heterochromatin. These results link receptor activity with the epigenetic mechanisms responsible for ensuring the expression of one odorant receptor per olfactory sensory neuron.
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Affiliation(s)
- Todd Ferreira
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Sarah R Wilson
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Yoon Gi Choi
- Functional Genomics Laboratory, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Davide Risso
- Department of Statistics, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Sandrine Dudoit
- Division of Biostatistics, University of California, Berkeley, Berkeley, CA 94720, USA; Department of Statistics, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Terence P Speed
- Department of Statistics, University of California, Berkeley, Berkeley, CA 94720, USA; Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville VIC 3050, Australia
| | - John Ngai
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; Functional Genomics Laboratory, University of California, Berkeley, Berkeley, CA 94720, USA.
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28
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Ngai J. Intrinsic activity of odorant receptors guides sensory map formation. Cell 2013; 154:1186-7. [PMID: 24034241 DOI: 10.1016/j.cell.2013.08.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Olfactory sensory neurons innervate the olfactory bulb in stereotyped patterns according to the odorant receptors they express. A study by Nakashima et al. in this issue demonstrates that the odorant receptor's level of intrinsic activity-in the absence of activating odorant-influences the guidance of olfactory axons to their targets.
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Affiliation(s)
- John Ngai
- Department of Molecular and Cell Biology, Helen Wills Neuroscience Institute and QB3 Functional Genomics Laboratory, University of California, Berkeley, Berkeley, CA 94720, USA.
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29
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To KW, Chan WC, Chan TO, Ngai J, Tung A, Ng S, Choo KL, Hui DS. Comparison of empirical continuous positive airway pressure (CPAP) treatment versus initial portable sleep monitoring followed by CPAP treatment for patients with suspected obstructive sleep apnoea. Intern Med J 2012; 42:e107-14. [PMID: 21118409 DOI: 10.1111/j.1445-5994.2010.02402.x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Polysomnography is labour-intensive for diagnosing obstructive sleep apnoea (OSA). We compared two algorithms for initiating continuous positive airway pressure (CPAP) treatment for patients with suspected OSA. METHODS Symptomatic OSA patients were randomised into either algorithm I or II. Algorithm I consisted of an empirical CPAP trial whereas algorithm II utilised an Apnea Risk Evaluation System, a wireless device applied on the forehead, for establishing a diagnosis before a CPAP trial for 3 weeks. Primary outcome was success of CPAP trial, defined as CPAP usage > 4 h/night and willingness to continue CPAP. Subjective usefulness of CPAP, accuracy of Apnea Risk Evaluation System versus polysomnography and CPAP adherence at 6 months were secondary end-points. RESULTS Altogether 138 patients in algorithm I and 110 patients in algorithm II completed the CPAP trial. There were no significant differences between these algorithms with respect to the primary end-point. The sensitivity and specificity of algorithm I versus II as a diagnostic test for OSA were 0.3, 0.8 versus 0.31, 1.00 respectively. In predicting CPAP adherence at 6 months, the likelihood ratio positive for algorithms I and II was 2.7 and 5.27 respectively. The mean (SE) time taken from the first consultation to the end of CPAP trial in algorithm I and algorithm II was 60 (2) and 98 (5) days, respectively, P < 0.01. CONCLUSION An ambulatory approach with portable sleep monitoring for diagnosing OSA before a CPAP trial can identify more patients who would adhere to CPAP at 6 months than empirical CPAP treatment alone.
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Affiliation(s)
- K W To
- Division of Respiratory Medicine, Department of Medicine and Therapeutics, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong, China
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30
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Logan DW, Brunet LJ, Webb WR, Cutforth T, Ngai J, Stowers L. Learned recognition of maternal signature odors mediates the first suckling episode in mice. Curr Biol 2012; 22:1998-2007. [PMID: 23041191 PMCID: PMC3494771 DOI: 10.1016/j.cub.2012.08.041] [Citation(s) in RCA: 116] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2012] [Revised: 06/07/2012] [Accepted: 08/24/2012] [Indexed: 01/20/2023]
Abstract
BACKGROUND Soon after birth, all mammals must initiate milk suckling to survive. In rodents, this innate behavior is critically dependent on uncharacterized maternally derived chemosensory ligands. Recently, the first pheromone sufficient to initiate suckling was isolated from the rabbit. Identification of the olfactory cues that trigger first suckling in the mouse would provide the means to determine the neural mechanisms that generate innate behavior. RESULTS Here we use behavioral analysis, metabolomics, and calcium imaging of primary sensory neurons and find no evidence of ligands with intrinsic bioactivity, such as pheromones, acting to promote first suckling in the mouse. Instead, we find that the initiation of suckling is dependent on variable blends of maternal "signature odors" that are learned and recognized prior to first suckling. CONCLUSIONS As observed with pheromone-mediated behavior, the response to signature odors releases innate behavior. However, this mechanism tolerates variability in both the signaling ligands and sensory neurons, which may maximize the probability that this first essential behavior is successfully initiated. These results suggest that mammalian species have evolved multiple strategies to ensure the onset of this critical behavior.
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Affiliation(s)
- Darren W Logan
- Department of Cell Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
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31
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Viringipurampeer IA, Ferreira T, DeMaria S, Yoon JJ, Shan X, Moosajee M, Gregory-Evans K, Ngai J, Gregory-Evans CY. Pax2 regulates a fadd-dependent molecular switch that drives tissue fusion during eye development. Hum Mol Genet 2012; 21:2357-69. [PMID: 22357656 DOI: 10.1093/hmg/dds056] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Tissue fusion is an essential morphogenetic mechanism in development, playing a fundamental role in developing neural tube, palate and the optic fissure. Disruption of genes associated with the tissue fusion can lead to congenital malformations, such as spina bifida, cleft lip/palate and ocular coloboma. For instance, the Pax2 transcription factor is required for optic fissure closure, although the mechanism of Pax2 action leading to tissue fusion remains elusive. This lack of information defining how transcription factors drive tissue morphogenesis at the cellular level is hampering new treatments options. Through loss- and gain-of-function analysis, we now establish that pax2 in combination with vax2 directly regulate the fas-associated death domain (fadd) gene. In the presence of fadd, cell proliferation is restricted in the developing eye through a caspase-dependent pathway. However, the loss of fadd results in a proliferation defect and concomitant activation of the necroptosis pathway through RIP1/RIP3 activity, leading to an abnormal open fissure. Inhibition of RIP1 with the small molecule drug necrostatin-1 rescues the pax2 eye fusion defect, thereby overcoming the underlying genetic defect. Thus, fadd has an essential physiological function in protecting the developing optic fissure neuroepithelium from RIP3-dependent necroptosis. This study demonstrates the molecular hierarchies that regulate a cellular switch between proliferation and the apoptotic and necroptotic cell death pathways, which in combination drive tissue morphogenesis. Furthermore, our data suggest that future therapeutic strategies may be based on small molecule drugs that can bypass the gene defects causing common congenital tissue fusion defects.
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Affiliation(s)
- Ishaq A Viringipurampeer
- Department of Ophthalmology and Visual Sciences, University of British Columbia, Vancouver, BC, Canada
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32
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Abstract
The olfactory system detects and discriminates myriad chemical structures across a wide range of concentrations. To meet this task, the system utilizes a large family of G protein–coupled receptors—the odorant receptors—which are the chemical sensors underlying the perception of smell. Interestingly, the odorant receptors are also involved in a number of developmental decisions, including the regulation of their own expression and the patterning of the olfactory sensory neurons' synaptic connections in the brain. This review will focus on the diverse roles of the odorant receptor in the function and development of the olfactory system.
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Affiliation(s)
- Shannon DeMaria
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA 94720, USA
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33
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Triballeau N, Van Name E, Laslier G, Cai D, Paillard G, Sorensen PW, Hoffmann R, Bertrand HO, Ngai J, Acher FC. High-potency olfactory receptor agonists discovered by virtual high-throughput screening: molecular probes for receptor structure and olfactory function. Neuron 2009; 60:767-74. [PMID: 19081373 DOI: 10.1016/j.neuron.2008.11.014] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2008] [Revised: 11/03/2008] [Accepted: 11/10/2008] [Indexed: 11/27/2022]
Abstract
The detection of diverse chemical structures by the vertebrate olfactory system is accomplished by the recognition of odorous ligands by their cognate receptors. In the present study, we used computational screening to discover novel high-affinity agonists of an olfactory G protein-coupled receptor that recognizes amino acid ligands. Functional testing of the top candidates validated several agonists with potencies higher than any of the receptor's known natural ligands. Computational modeling revealed molecular interactions involved in ligand binding and further highlighted interactions that have been conserved in evolutionarily divergent amino acid receptors. Significantly, the top compounds display robust activities as odorants in vivo and include a natural product that may be used to signal the presence of bacteria in the environment. Our virtual screening approach should be applicable to the identification of new bioactive molecules for probing the structure of chemosensory receptors and the function of chemosensory systems in vivo.
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Affiliation(s)
- Nicolas Triballeau
- Laboratoire de Chimie et de Biochimie Pharmacologiques et Toxicologiques, CNRS UMR-8601, Université Paris Descartes, 45 rue des Saints Pères, 75270 Paris Cedex 06, France
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34
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Ng SSS, Chan TO, To KW, Ngai J, Tung A, Ko FWS, Hui DSC. Validation of a portable recording device (ApneaLink) for identifying patients with suspected obstructive sleep apnoea syndrome. Intern Med J 2008; 39:757-62. [DOI: 10.1111/j.1445-5994.2008.01827.x] [Citation(s) in RCA: 104] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Luu P, Acher F, Bertrand HO, Ngai J. Odorant receptor specificities and receptor combinatorials: implications for olfactory coding. Chem Senses 2008; 30 Suppl 1:i97-8. [PMID: 15738215 DOI: 10.1093/chemse/bjh132] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Percy Luu
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA
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Ko FWS, Woo J, Tam W, Lai CKW, Ngai J, Kwok T, Hui DSC. Prevalence and risk factors of airflow obstruction in an elderly Chinese population. Eur Respir J 2008; 32:1472-8. [PMID: 18684847 DOI: 10.1183/09031936.00058708] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
It is common practice to use a forced expiratory volume in one second (FEV(1))/ forced vital capacity (FVC) ratio of <70% as evidence of airflow obstruction. As the FEV(1)/FVC ratio falls with age, the lower limit of normal range (LLN), defined as the bottom 5% in a health reference population, of FEV(1)/FVC ratio has been suggested as a better index to reduce over-diagnosis of chronic obstructive pulmonary disease (COPD), particularly in the elderly. However, there are no large scale studies that focus on the diagnosis of COPD in the elderly based on these definitions. The present prospective epidemiological study involved 1,149 elderly subjects aged > or =60 yrs in the community. Detailed questionnaires, pre- and post-bronchodilator spirometry were performed. In total, 1,008 subjects (mean age 74.2+/-6.4 yrs; 271 males) completed satisfactory spirometry testing. Airflow obstruction was present in 25.9% as defined by the post-bronchodilator FEV(1)/FVC ratio of <70% and in 12.4% defined by the LLN of FEV(1)/FVC ratio. Moderate COPD, at least, was found in 14.0% of patients according to the post-bronchodilator FEV(1)/FVC ratio of <70% and in 8.5% of patients according to LLN of FEV(1)/FVC ratio. In the present elderly Chinese population (mostly females, with low education level and previous exposure to biomass during formative years), the prevalence of chronic obstructive pulmonary disease varied markedly depending on definitions adopted. Further longitudinal studies are needed to determine the precise definition of chronic obstructive pulmonary disease.
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Affiliation(s)
- F W S Ko
- Dept of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong
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Scolnick JA, Cui K, Duggan CD, Xuan S, Yuan XB, Efstratiadis A, Ngai J. Role of IGF signaling in olfactory sensory map formation and axon guidance. Neuron 2008; 57:847-57. [PMID: 18367086 DOI: 10.1016/j.neuron.2008.01.027] [Citation(s) in RCA: 63] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2007] [Revised: 09/25/2007] [Accepted: 01/14/2008] [Indexed: 01/16/2023]
Abstract
Olfactory neurons project their axons to spatially invariant glomeruli in the olfactory bulb, forming an ordered pattern of innervation comprising the olfactory sensory map. A mirror symmetry exists within this map, such that neurons expressing a given receptor typically project to one glomerulus on the medial face and one glomerulus on the lateral face of the bulb. The mechanisms underlying an olfactory neuron's choice to project medially versus laterally remain largely unknown, however. Here we demonstrate that insulin-like growth factor (IGF) signaling is required for sensory innervation of the lateral olfactory bulb. Mutations that eliminate IGF signaling cause axons destined for targets in the lateral bulb to shift to ectopic sites on the ventral-medial surface. Using primary cultures of olfactory and cerebellar neurons, we further show that IGF is a chemoattractant for axon growth cones. Together these observations reveal a role of IGF signaling in sensory map formation and axon guidance.
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Affiliation(s)
- Jonathan A Scolnick
- Department of Molecular and Cell Biology, Helen Wills Neuroscience Institute, Functional Genomics Laboratory, University of California at Berkeley, Berkeley, CA 94720, USA
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Szpara ML, Vranizan K, Tai YC, Goodman CS, Speed TP, Ngai J. Analysis of gene expression during neurite outgrowth and regeneration. BMC Neurosci 2007; 8:100. [PMID: 18036227 PMCID: PMC2245955 DOI: 10.1186/1471-2202-8-100] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2007] [Accepted: 11/23/2007] [Indexed: 01/08/2023] Open
Abstract
Background The ability of a neuron to regenerate functional connections after injury is influenced by both its intrinsic state and also by extrinsic cues in its surroundings. Investigations of the transcriptional changes undergone by neurons during in vivo models of injury and regeneration have revealed many transcripts associated with these processes. Because of the complex milieu of interactions in vivo, these results include not only expression changes directly related to regenerative outgrowth and but also unrelated responses to surrounding cells and signals. In vitro models of neurite outgrowth provide a means to study the intrinsic transcriptional patterns of neurite outgrowth in the absence of extensive extrinsic cues from nearby cells and tissues. Results We have undertaken a genome-wide study of transcriptional activity in embryonic superior cervical ganglia (SCG) and dorsal root ganglia (DRG) during a time course of neurite outgrowth in vitro. Gene expression observed in these models likely includes both developmental gene expression patterns and regenerative responses to axotomy, which occurs as the result of tissue dissection. Comparison across both models revealed many genes with similar gene expression patterns during neurite outgrowth. These patterns were minimally affected by exposure to the potent inhibitory cue Semaphorin3A, indicating that this extrinsic cue does not exert major effects at the level of nuclear transcription. We also compared our data to several published studies of DRG and SCG gene expression in animal models of regeneration, and found the expression of a large number of genes in common between neurite outgrowth in vitro and regeneration in vivo. Conclusion Many gene expression changes undergone by SCG and DRG during in vitro outgrowth are shared between these two tissue types and in common with in vivo regeneration models. This suggests that the genes identified in this in vitro study may represent new candidates worthy of further study for potential roles in the therapeutic regrowth of neuronal connections.
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Affiliation(s)
- Moriah L Szpara
- Department of Molecular and Cell Biology, University of California, Berkeley, California, USA.
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Healy KE, Pollock J, Ngai J, Virdi AS, Sumner DR. Designer biomaterials: too much information? J Musculoskelet Neuronal Interact 2007; 7:336-337. [PMID: 18094501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Affiliation(s)
- K E Healy
- Department of Bioengineering, University of California at Berkeley, Berkeley, CA 94720, USA.
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Abstract
To better understand the molecular mechanisms governing oligodendrocyte (OL) differentiation, we have used gene profiling to quantitatively analyze gene expression in synchronously differentiating OLs generated from pure oligodendrocyte precursor cells in vitro. By comparing gene expression in these OLs to OLs generated in vivo, we discovered that the program of OL differentiation can progress normally in the absence of heterologous cell-cell interactions. In addition, we found that OL differentiation was unexpectedly prolonged and occurred in at least two sequential stages, each characterized by changes in distinct complements of transcription factors and myelin proteins. By disrupting the normal dynamic expression patterns of transcription factors regulated during OL differentiation, we demonstrated that these sequential stages of gene expression can be independently controlled. We also uncovered several genes previously uncharacterized in OLs that encode transmembrane, secreted, and cytoskeletal proteins that are as highly upregulated as myelin genes during OL differentiation. Last, by comparing genomic loci associated with inherited increased risk of multiple sclerosis (MS) to genes regulated during OL differentiation, we identified several new positional candidate genes that may contribute to MS susceptibility. These findings reveal a previously unexpected complexity to OL differentiation and suggest that an intrinsic program governs successive phases of OL differentiation as these cells extend and align their processes, ensheathe, and ultimately myelinate axons.
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Affiliation(s)
- Jason C Dugas
- Department of Neurobiology, Stanford University School of Medicine, Stanford, California 94305, USA.
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Abstract
BACKGROUND Vertebrate odorant receptors comprise three types of G protein-coupled receptors: the OR, V1R and V2R receptors. The OR superfamily contains over 1,000 genes in some mammalian species, representing the largest gene superfamily in the mammalian genome. RESULTS To facilitate an informed analysis of OR gene phylogeny, we identified the complete set of 143 OR genes in the zebrafish genome, as well as the OR repertoires in two pufferfish species, fugu (44 genes) and tetraodon (42 genes). Although the genomes analyzed here contain fewer genes than in mammalian species, the teleost OR genes can be grouped into a larger number of major clades, representing greater overall OR diversity in the fish. CONCLUSION Based on the phylogeny of fish and mammalian repertoires, we propose a model for OR gene evolution in which different ancestral OR genes or gene families were selectively lost or expanded in different vertebrate lineages. In addition, our calculations of the ratios of non-synonymous to synonymous codon substitutions among more recently expanding OR subgroups in zebrafish implicate residues that may be involved in odorant binding.
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Affiliation(s)
- Tyler S Alioto
- Department of Molecular and Cell Biology, Functional Genomics Laboratory, Helen Wills Neuroscience Institute, University of California, Berkeley, California 94720, USA
- Grup de Recerca en Informàtica Biomèdica, Institut Municipal d'Investigació Mèdica, Universitat Pompeu Fabra, Centre de Regulació Genòmica, Psg. Marítim 37-49, 08003 Barcelona, Spain
| | - John Ngai
- Department of Molecular and Cell Biology, Functional Genomics Laboratory, Helen Wills Neuroscience Institute, University of California, Berkeley, California 94720, USA
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Dybbs M, Ngai J, Kaplan JM. Using microarrays to facilitate positional cloning: identification of tomosyn as an inhibitor of neurosecretion. PLoS Genet 2005; 1:6-16. [PMID: 16103915 PMCID: PMC1183521 DOI: 10.1371/journal.pgen.0010002] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2005] [Accepted: 02/01/2005] [Indexed: 12/03/2022] Open
Abstract
Forward genetic screens have been used as a powerful strategy to dissect complex biological pathways in many model systems. A significant limitation of this approach has been the time-consuming and costly process of positional cloning and molecular characterization of the mutations isolated in these screens. Here, the authors describe a strategy using microarray hybridizations to facilitate positional cloning. This method relies on the fact that premature stop codons (i.e., nonsense mutations) constitute a frequent class of mutations isolated in screens and that nonsense mutant messenger RNAs are efficiently degraded by the conserved nonsense-mediated decay pathway. They validate this strategy by identifying two previously uncharacterized mutations: (1) tom-1, a mutation found in a forward genetic screen for enhanced acetylcholine secretion in Caenorhabditis elegans, and (2) an apparently spontaneous mutation in the hif-1 transcription factor gene. They further demonstrate the broad applicability of this strategy using other known mutants in C. elegans,Arabidopsis, and mouse. Characterization of tom-1 mutants suggests that TOM-1, the C. elegans ortholog of mammalian tomosyn, functions as an endogenous inhibitor of neurotransmitter secretion. These results also suggest that microarray hybridizations have the potential to significantly reduce the time and effort required for positional cloning. Genetic screens are commonly used to figure out which genes are involved in a biological process. The first step in a genetic screen is to isolate mutant animals that are defective in the process being studied. The next step is to find which of the thousands of genes has the mutation that causes the observed defect. Positional cloning, the tried-and-true method for locating mutations, is slow and expensive. The authors propose using microarray hybridizations to speed the process. Their approach relies on the fact that a large fraction of the mutations found in screens are the results of premature stop codons, a particularly severe type of mutation. In cells, messages containing premature stop codons are rapidly destroyed by a protective pathway, called nonsense-mediated decay, thus making them directly detectable by microarray hybridization. The authors apply this strategy retrospectively to known mutants in Caenorhabditis elegans, Arabidopsis, and mouse. They identify two uncharacterized mutations in C. elegans, including one, tom-1, found in a forward genetic screen for enhancers of neurotransmission. Interestingly, their characterization of tom-1 mutants suggests that the highly conserved protein tomosyn inhibits neurotransmission in neurons. This study shows that microarray hybridizations will help reduce the time and effort required for positional cloning.
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Affiliation(s)
- Michael Dybbs
- Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Department of Molecular and Cell Biology, Functional Genomics Laboratory, Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America
| | - John Ngai
- Department of Molecular and Cell Biology, Functional Genomics Laboratory, Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America
| | - Joshua M Kaplan
- Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- *To whom correspondence should be addressed. E-mail:
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Abstract
The identification of the chemical structure of an odorant by the vertebrate olfactory system is thought to occur through the combinatorial activity from multiple receptors, each tuned to recognize different chemical features. What are the molecular determinants underlying the selectivity of individual odorant receptors for their cognate ligands? To address this question, we performed molecular modeling and site-directed mutagenesis on the ligand-binding region of two orthologous amino acid odorant receptors belonging to the "C family" of G-protein-coupled receptors in goldfish and zebrafish. We identified the critical ligand-receptor interactions that afford ligand binding as well as selectivity for different amino acids. Moreover, predictions regarding binding pocket structure allowed us to alter, in a predictable manner, the receptor preferences for different ligands. These results reveal how this class of odorant receptor has evolved to accommodate ligands of varying chemical structure and further illuminate the molecular principles underlying ligand recognition and selectivity in this family of chemosensory receptors.
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Affiliation(s)
- Percy Luu
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, California 94720-3200, USA
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Weidinger G, Thorpe CJ, Wuennenberg-Stapleton K, Ngai J, Moon RT. The Sp1-related transcription factors sp5 and sp5-like act downstream of Wnt/beta-catenin signaling in mesoderm and neuroectoderm patterning. Curr Biol 2005; 15:489-500. [PMID: 15797017 DOI: 10.1016/j.cub.2005.01.041] [Citation(s) in RCA: 162] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2004] [Revised: 01/06/2005] [Accepted: 01/07/2005] [Indexed: 01/17/2023]
Abstract
BACKGROUND Wnt/beta-catenin signaling regulates many processes during vertebrate development, including patterning of the mesoderm along the dorso-ventral axis and patterning of the neuroectoderm along the anterior-posterior axis during gastrulation. However, relatively little is known about Wnt target genes mediating these effects. RESULTS Using zebrafish DNA microarrays, we have identified several new targets of Wnt/beta-catenin signaling, including sp5-like (sp5l, previously called spr2), a zinc-finger transcription factor of the Sp1 family. sp5-like is a direct target of Wnt/beta-catenin signaling and acts together with its paralog sp5 (previously called bts1) downstream of wnt8 in patterning of the mesoderm and neuroectoderm because (1) overexpression of sp5-like, like overexpression of wnt8, posteriorizes the neuroectoderm, (2) sp5-like morpholino-mediated knockdown, like wnt8 knockdown, causes anteriorization of the hindbrain, (3) combined knockdown of sp5 and sp5-like, like loss of wnt8, causes expansion of dorsal mesoderm, (4) sp5-like knockdown reduces the defects in mesoderm and neuroectoderm patterning caused by wnt8 overexpression, and (5) inhibition of sp5-like enhances the effects of hypomorphic loss of wnt8. Importantly, (6) overexpression of sp5-like is able to partially restore normal hindbrain patterning in wnt8 morphants. CONCLUSIONS sp5-like is a direct target of Wnt/beta-catenin signaling during gastrulation and, together with sp5, acts as a required mediator of the activities of wnt8 in patterning the mesoderm and neuroectoderm. We conclude that sp5 transcription factors mediate the downstream responses to Wnt/beta-catenin signaling in several developmental processes in zebrafish.
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Affiliation(s)
- Gilbert Weidinger
- Howard Hughes Medical Institute, Department of Pharmacology and Center for Developmental Biology, University of Washington School of Medicine, Box 357370, Seattle, Washington 98195, USA
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Lin DM, Yang YH, Scolnick JA, Brunet LJ, Marsh H, Peng V, Okazaki Y, Hayashizaki Y, Speed TP, Ngai J. Spatial patterns of gene expression in the olfactory bulb. Proc Natl Acad Sci U S A 2004; 101:12718-23. [PMID: 15304640 PMCID: PMC515121 DOI: 10.1073/pnas.0404872101] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
How olfactory sensory neurons converge on spatially invariant glomeruli in the olfactory bulb is largely unknown. In one model, olfactory sensory neurons interact with spatially restricted guidance cues in the bulb that orient and guide them to their target. Identifying differentially expressed molecules in the olfactory bulb has been extremely difficult, however, hindering a molecular analysis of convergence. Here, we describe several such genes that have been identified in a screen that compiled microarray data to create a three-dimensional model of gene expression within the mouse olfactory bulb. The expression patterns of these identified genes form the basis of a nascent spatial map of differential gene expression in the bulb.
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Affiliation(s)
- David M Lin
- Department of Molecular and Cell Biology, Functional Genomics Laboratory, Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA
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Ngai J. Science imitates art: the cloning of mice from olfactory sensory neurons. Cell 2004; 116:636-7. [PMID: 15006346 DOI: 10.1016/s0092-8674(04)00212-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The functional identity of an olfactory sensory neuron is defined by its expression of one odorant receptor from a large multigene family. The complexity of this process has led to speculation that DNA rearrangements are used to limit the expression of one receptor gene per cell. However, a recent report in Nature directly rules out irreversible DNA rearrangements as a mechanism for odorant receptor gene choice.
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Affiliation(s)
- John Ngai
- Department of Molecular and Cell Biology, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
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Díaz E, Yang YH, Ferreira T, Loh KC, Okazaki Y, Hayashizaki Y, Tessier-Lavigne M, Speed TP, Ngai J. Analysis of gene expression in the developing mouse retina. Proc Natl Acad Sci U S A 2003; 100:5491-6. [PMID: 12702772 PMCID: PMC154372 DOI: 10.1073/pnas.0831080100] [Citation(s) in RCA: 40] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
In the visual system, differential gene expression underlies development of the anterior-posterior and dorsal-ventral axes. Here we present the results of a microarray screen to identify genes differentially expressed in the developing retina. We assayed gene expression in nasal (anterior), temporal (posterior), dorsal, and ventral embryonic mouse retina. We used a statistical method to estimate gene expression between different retina regions. Genes were clustered according to their expression pattern and were ranked within each cluster. We identified groups of genes expressed in gradients or with restricted patterns of expression as verified by in situ hybridization. A common theme for the identified genes is the differential expression in the dorsal-ventral axis. By analyzing gene expression patterns, we provide insight into the molecular organization of the developing retina.
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Affiliation(s)
- Elva Díaz
- Department of Molecular and Cell Biology, Functional Genomics Laboratory, Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720, USA
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Díaz E, Ge Y, Yang YH, Loh KC, Serafini TA, Okazaki Y, Hayashizaki Y, Speed TP, Ngai J, Scheiffele P. Molecular analysis of gene expression in the developing pontocerebellar projection system. Neuron 2002; 36:417-34. [PMID: 12408845 DOI: 10.1016/s0896-6273(02)01016-4] [Citation(s) in RCA: 74] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
Abstract
As an approach toward understanding the molecular mechanisms of neuronal differentiation, we utilized DNA microarrays to elucidate global patterns of gene expression during pontocerebellar development. Through this analysis, we identified groups of genes specific to neuronal precursor cells, associated with axon outgrowth, and regulated in response to contact with synaptic target cells. In the cerebellum, we identified a phase of granule cell differentiation that is independent of interactions with other cerebellar cell types. Analysis of pontine gene expression revealed that distinct programs of gene expression, correlated with axon outgrowth and synapse formation, can be decoupled and are likely influenced by different cells in the cerebellar target environment. Our approach provides insight into the genetic programs underlying the differentiation of specific cell types in the pontocerebellar projection system.
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Affiliation(s)
- Elva Díaz
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA
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