309 – 323 (2014). doi:10.1016/j.neuron.2014.05.033;
pmid: 24952961
- 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 - J. A. Milleret al., Transcriptional landscape of the prenatal
human brain.Nature 508 , 199–206 (2014). doi:10.1038/
nature13185; pmid: 24695229 - 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 - 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 - 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 - 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 - 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 - 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 - 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 - H. Markram, The human brain project.Sci. Am. 306 ,50–55 (2012).
doi:10.1038/scientificamerican0612-50;pmid: 22649994 - 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 - A. Regevet al., The Human Cell Atlas.eLife 6 , e27041 (2017).
doi:10.7554/eLife.27041; pmid: 29206104 - The HPA Brain Atlas;www.proteinatlas.org/brain.
- GTEx Consortium, Genetic effects on gene expression across
human tissues.Nature 550 , 204–213 (2017). doi:10.1038/
nature24277; pmid: 29022597 - S. Noguchiet al., FANTOM5 CAGE profiles of human and
mouse samples.Sci. Data 4 , 170112 (2017). doi:10.1038/
sdata.2017.112; pmid: 28850106 - 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 - J. Lovénet al., Revisiting global gene expression analysis.
Cell 151 , 476–482 (2012). doi:10.1016/j.cell.2012.10.012;
pmid: 23101621 - 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 - 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 - 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 - 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 - 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 - 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 - 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
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