Science 6.03.2020

(Nancy Kaufman) #1
309 – 323 (2014). doi:10.1016/j.neuron.2014.05.033;
pmid: 24952961


  1. M. J. Hawrylyczet al., An anatomically comprehensive atlas of
    the adult human brain transcriptome.Nature 489 , 391– 399
    (2012). doi:10.1038/nature11405; pmid: 22996553

  2. J. A. Milleret al., Transcriptional landscape of the prenatal
    human brain.Nature 508 , 199–206 (2014). doi:10.1038/
    nature13185; pmid: 24695229

  3. Y. Zhanget al., An RNA-sequencing transcriptome and splicing
    database of glia, neurons, and vascular cells of the cerebral
    cortex.J. Neurosci. 34 , 11929–11947 (2014). doi:10.1523/
    JNEUROSCI.1860-14.2014; pmid: 25186741

  4. Y. Zhanget al., Purification and characterization of progenitor
    and mature human astrocytes reveals transcriptional and
    functional differences with mouse.Neuron 89 ,37–53 (2016).
    doi:10.1016/j.neuron.2015.11.013; pmid: 26687838

  5. A. Zeiselet al., Molecular architecture of the mouse nervous
    system.Cell 174 , 999–1014.e22 (2018). doi:10.1016/
    j.cell.2018.06.021; pmid: 30096314

  6. B. B. Lakeet al., Integrative single-cell analysis of transcriptional
    and epigenetic states in the human adult brain.Nat. Biotechnol. 36 ,
    70 – 80 (2018). doi:10.1038/nbt.4038;pmid: 29227469

  7. R. D. Hodgeet al., Conserved cell types with divergent features
    in human versus mouse cortex.Nature 573 ,61–68 (2019).
    doi:10.1038/s41586-019-1506-7; pmid: 31435019

  8. K. W. Kelley, H. Nakao-Inoue, A. V. Molofsky, M. C. Oldham,
    Variation among intact tissue samples reveals the core
    transcriptional featuresof human CNS cell classes.
    Nat. Neurosci. 21 , 1171–1184 (2018). doi:10.1038/s41593-018-
    0216-z; pmid: 30154505

  9. J. R. Eckeret al., The BRAIN Initiative Cell Census Consortium:
    Lessons learned toward generating a comprehensive brain
    cell atlas.Neuron 96 , 542–557 (2017). doi:10.1016/
    j.neuron.2017.10.007; pmid: 29096072

  10. H. Markram, The human brain project.Sci. Am. 306 ,50–55 (2012).
    doi:10.1038/scientificamerican0612-50;pmid: 22649994

  11. HuBMAP Consortium, The human body at cellular resolution: The
    NIH Human Biomolecular Atlas Program.Nature 574 ,187– 192
    (2019). doi:10.1038/s41586-019-1629-x; pmid: 31597973

  12. A. Regevet al., The Human Cell Atlas.eLife 6 , e27041 (2017).
    doi:10.7554/eLife.27041; pmid: 29206104

  13. The HPA Brain Atlas;www.proteinatlas.org/brain.

  14. GTEx Consortium, Genetic effects on gene expression across
    human tissues.Nature 550 , 204–213 (2017). doi:10.1038/
    nature24277; pmid: 29022597

  15. S. Noguchiet al., FANTOM5 CAGE profiles of human and
    mouse samples.Sci. Data 4 , 170112 (2017). doi:10.1038/
    sdata.2017.112; pmid: 28850106

  16. J. E. Coate, J. J. Doyle, Variation in transcriptome size: Are we
    getting the message?Chromosoma 124 ,27–43 (2015).
    doi:10.1007/s00412-014-0496-3; pmid: 25421950

  17. J. Lovénet al., Revisiting global gene expression analysis.
    Cell 151 , 476–482 (2012). doi:10.1016/j.cell.2012.10.012;
    pmid: 23101621

  18. M.D. Robinson, A. Oshlack, A scaling normalization method for
    differential expression analysis of RNA-seq data.Genome Biol.
    11 , R25 (2010). doi:10.1186/gb-2010-11-3-r25;pmid: 20196867

  19. R. A. van den Berg, H. C. Hoefsloot, J. A. Westerhuis,
    A. K. Smilde, M. J. van der Werf, Centering, scaling, and
    transformations: Improving the biological information content
    of metabolomics data.BMC Genomics 7 , 142 (2006).
    doi:10.1186/1471-2164-7-142; pmid: 16762068

  20. M. E. Ritchieet al.,limmapowers differential expression
    analyses for RNA-sequencing and microarray studies.
    Nucleic Acids Res. 43 , e47 (2015). doi:10.1093/nar/gkv007;
    pmid: 25605792

  21. J. C. Corvol, J. M. Studler, J. S. Schonn, J. A. Girault, D. Hervé,
    Gaolfis necessary for coupling D1 and A2a receptors to adenylyl
    cyclase in the striatum.J. Neurochem. 76 , 1585–1588 (2001).
    doi:10.1046/j.1471-4159.2001.00201.x; pmid: 11238742

  22. I. H. Kimet al., Evidence for functional diversity between the
    voltage-gated proton channel Hv1 and its closest related
    protein HVRP1.PLOS ONE 9 , e105926 (2014). doi:10.1371/
    journal.pone.0105926; pmid: 25165868

  23. N. Zainolabidin, S. P. Kamath, A. R. Thanawalla, A. I. Chen,
    Distinct activities of Tfap2A and Tfap2B in the specification of
    GABAergic interneurons in the developing cerebellum.Front.
    Mol. Neurosci. 10 , 281 (2017). doi:10.3389/fnmol.2017.00281;
    pmid: 28912684

  24. J. Mulderet al., Secretagogin is a Ca2+-binding protein
    specifying subpopulations of telencephalic neurons.Proc. Natl.
    Acad. Sci. U.S.A. 106 , 22492–22497 (2009). doi:10.1073/
    pnas.0912484106; pmid: 20018755
    29. E. S. Deneris, O. Hobert, Maintenance of postmitotic neuronal
    cell identity.Nat. Neurosci. 17 , 899–907 (2014). doi:10.1038/
    nn.3731; pmid: 24929660
    30. H. Guoet al., Specificity and efficiency of Cre-mediated
    recombination in Emx1-Cre knock-in mice.Biochem. Biophys.
    Res. Commun. 273 , 661–665 (2000). doi:10.1006/
    bbrc.2000.2870; pmid: 10873661
    31. P. S. Joshiet al., Bhlhb5 regulates the postmitotic acquisition
    of area identities in layers II-V of the developing neocortex.
    Neuron 60 , 258–272 (2008). doi:10.1016/
    j.neuron.2008.08.006; pmid: 18957218
    32. D. Jean, G. Bernier, P. Gruss,Six6(Optx2) is a novel murine
    Six3-related homeobox gene that demarcates the presumptive
    pituitary/hypothalamic axis and the ventral optic stalk.Mech.
    Dev. 84 ,31–40 (1999). doi:10.1016/S0925-4773(99)00068-4;
    pmid: 10473118
    33. I. Nunes, L. T. Tovmasian, R. M. Silva, R. E. Burke, S. P. Goff, Pitx3
    is required for development of substantia nigra dopaminergic
    neurons.Proc. Natl. Acad. Sci. U.S.A. 100 ,4245–4250 (2003).
    doi:10.1073/pnas.0230529100; pmid: 12655058
    34. F. Chantoux, J. Francon, Thyroid hormone regulates the
    expression of NeuroD/BHF1 during the development of rat
    cerebellum.Mol. Cell. Endocrinol. 194 , 157–163 (2002).
    doi:10.1016/S0303-7207(02)00133-8; pmid: 12242038
    35. R. Grailheet al., Increased exploratory activity and altered
    response to LSD in mice lacking the 5-HT(5A) receptor.Neuron
    22 , 581–591 (1999). doi:10.1016/S0896-6273(00)80712-6;
    pmid: 10197537
    36. R.Grailhe, G. W. Grabtree, R. Hen, Human 5-HT(5) receptors:
    The 5-HT(5A) receptor is functional but the 5-HT(5B) receptor
    was lost during mammalian evolution.Eur. J. Pharmacol. 418 ,
    157 – 167 (2001). doi:10.1016/S0014-2999(01)00933-5;
    pmid: 11343685
    37. R. L. Smith, H. Baker, K. Kolstad, D. D. Spencer, C. A. Greer,
    Localization of tyrosine hydroxylase and olfactory marker
    protein immunoreactivities in the human and macaque
    olfactory bulb.Brain Res. 548 ,140–148 (1991). doi:10.1016/
    0006-8993(91)91115-H; pmid: 1678294
    38. M. Lebel, Y. Gauthier, A. Moreau, J. Drouin, Pitx3 activates
    mouse tyrosine hydroxylase promoter via a high-affinity
    binding site.J. Neurochem. 77 , 558–567 (2001). doi:10.1046/
    j.1471-4159.2001.00257.x; pmid: 11299318
    39. E. Mezey, Phenylethanolamine N-methyltransferase-containing
    neurons in the limbic system of the young rat.Proc. Natl. Acad.
    Sci. U.S.A. 86 , 347–351 (1989). doi:10.1073/pnas.86.1.347;
    pmid: 2563164
    40. N. Puskás, R. S. Papp, K. Gallatz, M. Palkovits, Interactions
    between orexin-immunoreactive fibers and adrenaline or
    noradrenaline-expressing neurons of the lower brainstem in
    rats and mice.Peptides 31 , 1589–1597 (2010). doi:10.1016/
    j.peptides.2010.04.020; pmid: 20434498
    41. L. C. Daws, G. G. Gould, Ontogeny and regulation of the
    serotonin transporter: Providing insights into human disorders.
    Pharmacol. Ther. 131 ,61–79 (2011). doi:10.1016/
    j.pharmthera.2011.03.013; pmid: 21447358
    42. J. Peng, S. Sarkar, S. L. Chang, Opioid receptor expression in
    human brain and peripheral tissues using absolute quantitative
    real-time RT-PCR.Drug Alcohol Depend. 124 , 223–228 (2012).
    doi:10.1016/j.drugalcdep.2012.01.013; pmid: 22356890
    43. D. L. Kaufmanet al., Characterization of the murinemopioid
    receptor gene.J. Biol. Chem. 270 , 15877–15883 (1995).
    doi:10.1074/jbc.270.26.15877; pmid: 7797593
    44. M.Mortensen, B. Patel, T. G. Smart, GABA potency at GABA(A)
    receptors found in synaptic and extrasynaptic zones.Front.
    Cell. Neurosci. 6 , 1 (2012). pmid: 22319471
    45. X. Gondaet al., A new stress sensor and risk factor for suicide:
    The T allele of the functional genetic variant in the GABRA6
    gene.Sci. Rep. 7 , 12887 (2017). doi:10.1038/s41598-017-
    12776-8; pmid: 29018204
    46. A. S. Hauser, M. M. Attwood, M. Rask-Andersen, H. B. Schiöth,
    D. E. Gloriam, Trends in GPCR drug discovery: New agents,
    targets and indications.Nat. Rev. Drug Discov. 16 , 829– 842
    (2017). doi:10.1038/nrd.2017.178; pmid: 29075003
    47. K. Mizushimaet al., A novel G-protein-coupled receptor gene
    expressed in striatum.Genomics 69 ,314–321 (2000).
    doi:10.1006/geno.2000.6340; pmid: 11056049
    48. D. M. Berson, F. A. Dunn, M. Takao, Phototransduction by retinal
    ganglion cells that set the circadian clock.Science 295 , 1070– 1073
    (2002). doi:10.1126/science.1067262;pmid:11834835
    49.M.N.Moraeset al., Melanopsin, a canonical light receptor,
    mediates thermal activation of clock genes.Sci. Rep. 7 ,
    13977 (2017). doi:10.1038/s41598-017-13939-3;
    pmid: 29070825
    50. M. Uhlenet al., A genome-wide transcriptomic analysis of
    protein-coding genes in human blood cells.Science 366 , eaax9198
    (2019). doi:10.1126/science.aax9198;pmid:31857451
    51. E. Sjöstedtet al., Defining the human brain proteome using
    transcriptomics and antibody-based profiling with a focus on
    the cerebral cortex.PLOS ONE 10 , e0130028 (2015).
    doi:10.1371/journal.pone.0130028; pmid: 26076492
    52. M. W. Vermuntet al., Epigenomic annotation of gene
    regulatory alterations during evolution of the primate brain.
    Nat. Neurosci. 19 , 494–503 (2016). doi:10.1038/nn.4229;
    pmid: 26807951
    53. H. Takahashi, S. Kato, M. Murata, P. Carninci, CAGE (cap
    analysis of gene expression): A protocol for the detection of
    promoter and transcriptional networks.Methods Mol. Biol.
    786 ,181–200 (2012). doi:10.1007/978-1-61779-292-2_11;
    pmid: 21938627
    54. D. R. Zerbinoet al., Ensembl 2018.Nucleic Acids Res. 46 ,
    D754–D761 (2018). doi:10.1093/nar/gkx1098;
    pmid: 29155950
    55. N. L. Bray, H. Pimentel, P. Melsted, L. Pachter, Near-optimal
    probabilistic RNA-seq quantification.Nat. Biotechnol. 34 ,
    525 – 527 (2016). doi:10.1038/nbt.3519; pmid: 27043002
    56. R Core Team, R: A language and environment for statistical
    computing (R Foundation for Statistical Computing, 2018);
    http://www.R-project.org.
    57. C. Spearman, The proof and measurement of association
    between two things. By C. Spearman, 1904.Am. J. Psychol.
    100 , 441–471 (1987). doi:10.2307/1422689; pmid: 3322052
    58. L. Kaufman, P. J. Rousseeuw, Finding Groups in Data: An
    Introduction to Cluster analysis(Wiley Series in Probability
    and Statistics, Wiley, 1990).
    59. F. Murtagh, P. Legendre, Ward’s hierarchical agglomerative
    clustering method: Which algorithms implement Ward’s
    criterion?J. Classif. 31 , 274–295 (2014). doi:10.1007/s00357-
    014-9161-z
    60. S. Bhattacharyaet al., ImmPort, toward repurposing of open
    access immunological assay data for translational and
    clinical research.Sci. Data 5 , 180015 (2018). doi:10.1038/
    sdata.2018.15; pmid: 29485622
    61. L. McInnes, J. Healy, J. Melville, UMAP: Uniform Manifold
    Approximation and Projection for Dimension Reduction.
    arXiv:1802.03426[stat.ML] (9 February 2018).
    62. C. Kampf, I. Olsson, U. Ryberg, E. Sjöstedt, F. Pontén,
    Production of tissue microarrays, immunohistochemistry
    staining and digitalization within the Human Protein Atlas.
    J. Vis. Exp.10.3791/3620 (2012). doi:10.3791/3620;
    pmid: 22688270
    63. J. Mulderet al., Tissue profiling of the mammalian central
    nervous system using human antibody-based proteomics.
    Mol. Cell. Proteomics 8 , 1612–1622 (2009).doi:10.1074/
    mcp.M800539-MCP200; pmid: 19351664
    64. N. Renieret al., Mapping of brain activity by automated volume
    analysis of immediate early genes.Cell 165 , 1789–1802 (2016).
    doi:10.1016/j.cell.2016.05.007; pmid: 27238021


ACKNOWLEDGMENTS
We thank W. Gu from the School of Biotechnology, Southern Medical
University, Guangzhou, for providing the pigs. We acknowledge the
entire staff of the Human Protein Atlas program and the Science for
Life Laboratory for their valuable contributions. Support from the
National Genomics Infrastructure in Stockholm is acknowledged,
with funding from Science for Life Laboratory, the Knut and Alice
Wallenberg Foundation, the Swedish Research Council, and SNIC/
Uppsala Multidisciplinary Center for Advanced Computational
Science for assistance with massively parallel sequencing and access
to the UPPMAX computational infrastructure.Funding:Main
funding was provided by the Knut and Alice Wallenberg Foundation
(WCPR) and the Erling Persson Foundation (KCAP). The pig atlas
part is supported by Sanming Project of Medicine in Shenzhen
(SZSM201612074). L.L. is supported by the Lundbeck Foundation
(R219–2016-1375) and the DFF Sapere Aude Starting grant
(8048-00072A).Author contributions:M.U. and J.M. conceived
of and designed the study. J.H., Y.D., L.L., Z.D., X.L., H.J., and
Y.L. performed pig brain experiments (sample processing, RNA
extraction, quality control, NGS library constructions, sequencing,
and pilot data analysis). W.Z., L.F., M.K., A.M., and C.Z. performed
the bioinformatics analysis. K.v.F. and P.O. provided the infrastructure
for the data. E.S., M.U., W.Z., T.H., and J.M. drafted the manuscript.
All authors discussed the results and contributed to the final
manuscript.Competing interests:T.H. has shares in Lundbeck
and Bioarctic. No other authors declare any competing interests.
Data and materials availability:Materials are available upon
request from J.M. All classification information, data, and gene

Sjöstedtet al.,Science 367 , eaay5947 (2020) 6 March 2020 15 of 16


RESEARCH | RESEARCH ARTICLE

Free download pdf