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Comprehensive transcriptome analysis of neocortical layers in humans, chimpanzees and macaques

Nature Neuroscience volume 20, pages 886895 (2017) | Download Citation

Abstract

While human cognitive abilities are clearly unique, underlying changes in brain organization and function remain unresolved. Here we characterized the transcriptome of the cortical layers and adjacent white matter in the prefrontal cortexes of humans, chimpanzees and rhesus macaques using unsupervised sectioning followed by RNA sequencing. More than 20% of detected genes were expressed predominantly in one layer, yielding 2,320 human layer markers. While the bulk of the layer markers were conserved among species, 376 switched their expression to another layer in humans. By contrast, only 133 of such changes were detected in the chimpanzee brain, suggesting acceleration of cortical reorganization on the human evolutionary lineage. Immunohistochemistry experiments further showed that human-specific expression changes were not limited to neurons but affected a broad spectrum of cortical cell types. Thus, despite apparent histological conservation, human neocortical organization has undergone substantial changes affecting more than 5% of its transcriptome.

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References

  1. 1.

    & The emergence and evolution of mammalian neocortex. Trends Neurosci. 18, 373–379 (1995).

  2. 2.

    & Degree of automaticity and the prefrontal cortex. Trends Cogn. Sci. 19, 244–250 (2015).

  3. 3.

    & Two principles of organization in the prefrontal cortex are cognitive hierarchy and degree of automaticity. Nat. Commun. 4, 2041 (2013).

  4. 4.

    , , & Evolution of primate gene expression. Nat. Rev. Genet. 7, 693–702 (2006).

  5. 5.

    et al. Transcriptional neoteny in the human brain. Proc. Natl. Acad. Sci. USA 106, 5743–5748 (2009).

  6. 6.

    et al. Extension of cortical synaptic development distinguishes humans from chimpanzees and macaques. Genome Res. 22, 611–622 (2012).

  7. 7.

    The evolution of the brain, the human nature of cortical circuits, and intellectual creativity. Front. Neuroanat. 5, 29 (2011).

  8. 8.

    et al. A transcriptomic atlas of mouse neocortical layers. Neuron 71, 605–616 (2011).

  9. 9.

    , , & High quality RNA from multiple brain regions simultaneously acquired by laser capture microdissection. BMC Mol. Biol. 10, 69 (2009).

  10. 10.

    et al. Transcriptional architecture of the primate neocortex. Neuron 73, 1083–1099 (2012).

  11. 11.

    et al. Genome-wide atlas of gene expression in the adult mouse brain. Nature 445, 168–176 (2007).

  12. 12.

    et al. Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures. Cell 149, 483–496 (2012).

  13. 13.

    et al. High spatial resolution proteomic comparison of the brain in humans and chimpanzees. J. Comp. Neurol. 523, 2043–2061 (2015).

  14. 14.

    , & Sectioning of brain tissues. Cold Spring Harb. Protoc. 2008, ip42 (2008).

  15. 15.

    et al. Spatial transcriptome for the molecular annotation of lineage fates and cell identity in mid-gastrula mouse embryo. Dev. Cell 36, 681–697 (2016).

  16. 16.

    , , , & Conserved expression of lincRNA during human and macaque prefrontal cortex development and maturation. RNA 20, 1103–1111 (2014).

  17. 17.

    et al. Unique transcriptome patterns of the white and grey matter corroborate structural and functional heterogeneity in the human frontal lobe. PLoS One 8, e78480 (2013).

  18. 18.

    Layer-specific markers as probes for neuron type identity in human neocortex and malformations of cortical development. J. Neuropathol. Exp. Neurol. 66, 101–109 (2007).

  19. 19.

    et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 12, 453–457 (2015).

  20. 20.

    et al. A survey of human brain transcriptome diversity at the single cell level. Proc. Natl. Acad. Sci. USA 112, 7285–7290 (2015).

  21. 21.

    , , & Neocortical glial cell numbers in human brains. Neurobiol. Aging 29, 1754–1762 (2008).

  22. 22.

    The human brain in numbers: a linearly scaled-up primate brain. Front. Hum. Neurosci. 3, 31 (2009).

  23. 23.

    , & RNA content in the neurons and glia of the hypothalamic nuclei after intermittent cooling. Neurosci. Behav. Physiol. 7, 69–71 (1976).

  24. 24.

    et al. Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain. Science 352, 1586–1590 (2016).

  25. 25.

    et al. Laminar and temporal expression dynamics of coding and noncoding RNAs in the mouse neocortex. Cell Rep. 6, 938–950 (2014).

  26. 26.

    & A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 4, e17 (2005).

  27. 27.

    et al. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J. Neurosci. 34, 11929–11947 (2014).

  28. 28.

    et al. Proteomics. Tissue-based map of the human proteome. Science 347, 1260419 (2015).

  29. 29.

    & Neocortical arealization: evolution, mechanisms, and open questions. Dev. Neurobiol. 73, 411–447 (2013).

  30. 30.

    The evolution of brains from early mammals to humans. Wiley Interdiscip. Rev. Cogn. Sci. 4, 33–45 (2013).

  31. 31.

    , & Ancestry of the mammalian preplate and its derivatives: evolutionary relicts or embryonic adaptations? Rev. Neurosci. 16, 359–376 (2005).

  32. 32.

    , & Developmental history of the subplate zone, subplate neurons and interstitial white matter neurons: relevance for schizophrenia. Int. J. Dev. Neurosci. 29, 193–205 (2011).

  33. 33.

    , & Development of the human cerebral cortex: Boulder Committee revisited. Nat. Rev. Neurosci. 9, 110–122 (2008).

  34. 34.

    , , & Secondary expansion of the transient subplate zone in the developing cerebrum of human and nonhuman primates. Proc. Natl. Acad. Sci. USA 113, 9892–9897 (2016).

  35. 35.

    , & Molecular cloning and expression regulation of PRG-3, a new member of the plasticity-related gene family. Eur. J. Neurosci. 19, 212–220 (2004).

  36. 36.

    , & Cloning of a novel Olf-1/EBF-like gene, O/E-4, by degenerate oligo-based direct selection. Mol. Cell. Neurosci. 20, 404–414 (2002).

  37. 37.

    Brodmann's Localisation in the Cerebral Cortex (Springer, 2006).

  38. 38.

    Lateral prefrontal cortex: architectonic and functional organization. Philos. Trans. R. Soc. Lond. B. Biol. Sci. 360, 781–795 (2005).

  39. 39.

    et al. The organization of dorsal frontal cortex in humans and macaques. J. Neurosci. 33, 12255–12274 (2013).

  40. 40.

    , & Atlas of the Human Brain 4th edn. (Elsevier, 2016).

  41. 41.

    , , & The Rhesus Monkey Brain in Stereotaxic Coordinates 2nd edn. (Elsevier, 2009).

  42. 42.

    & Cytoarchitectonic definition of prefrontal areas in the normal human cortex: I. Remapping of areas 9 and 46 using quantitative criteria. Cereb. Cortex 5, 307–322 (1995).

  43. 43.

    , , , & Prefrontal cortex in humans and apes: a comparative study of area 10. Am. J. Phys. Anthropol. 114, 224–241 (2001).

  44. 44.

    et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

  45. 45.

    et al. Measure transcript integrity using RNA-seq data. BMC Bioinformatics 17, 58 (2016).

  46. 46.

    et al. Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347, 1138–1142 (2015).

  47. 47.

    , & Glial fibrillary acidic protein in astrocytes in the human neocortex. Neurosci. Behav. Physiol. 35, 789–792 (2005).

  48. 48.

    , , , & Immunohistochemical markers for quantitative studies of neurons and glia in human neocortex. J. Histochem. Cytochem. 56, 201–221 (2008).

  49. 49.

    , & Reduction of lipofuscin-like autofluorescence in fluorescently labeled tissue. J. Histochem. Cytochem. 47, 719–730 (1999).

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Acknowledgements

We thank the Maryland Brain Collection Center and the Chinese Brain Bank Center for providing the human samples; the Biomedical Primate Research Centre, the Burgers' Zoo in Arnhem, and R. Martin and W. Scheffran (Zurich University, Anthropology Department, Zurich, Switzerland) for providing the chimpanzee samples; and the Suzhou Drug Safety Evaluation and Research Center and C. Lian, H. Cai and X. Zheng for providing the macaque samples. We thank G.L. Banes for his comments on the manuscript. This study was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (grant XDB13010200 to P.K.); the National Natural Science Foundation of China (grants 91331203, 31171232, 31501047 and 31420103920 to P.K.); the National One Thousand Foreign Experts Plan (grant WQ20123100078 to P.K.); the Bureau of International Cooperation, Chinese Academy of Sciences (grant GJHZ201313 to P.K.); and the Russian Science Foundation (grant 16-14-00220 to P.K.).

Author information

Author notes

    • Zhisong He
    •  & Dingding Han

    These authors contributed equally to this work.

Affiliations

  1. CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, SIBS, CAS, Shanghai, China.

    • Zhisong He
    • , Dingding Han
    • , Patricia Guijarro
    • , Qianhui Yu
    • , Anna Oleksiak
    • , Shasha Jiang
    •  & Stefan Grünewald
  2. Big Data Decision Institute, Jinan University, Guangzhou, China.

    • Dingding Han
  3. Skolkovo Institute of Science and Technology, Skolkovo, Russia.

    • Olga Efimova
    •  & Philipp Khaitovich
  4. University of Chinese Academy of Sciences, Beijing, China.

    • Qianhui Yu
  5. Department of Neuroscience, National Research Center, Kurchatov Institute, Moscow, Russia.

    • Konstantin Anokhin
  6. School of Life Science and Technology, ShanghaiTech University, Shanghai, China.

    • Boris Velichkovsky
    •  & Philipp Khaitovich
  7. Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.

    • Philipp Khaitovich
  8. Immanuel Kant Baltic Federal University, Kaliningrad, Russia.

    • Philipp Khaitovich
  9. Comparative Biology group, PICB, SIBS, CAS, Shanghai, China.

    • Philipp Khaitovich

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Contributions

P.K. conceived the project and designed the experiment. Z.H. and Q.Y. designed and executed the bioinformatics analysis. Z.H. designed and executed the bioinformatics analysis. D.H. made sequencing libraries and performed qPCR and LCM experiments. O.E. performed immunohistochemistry experiments. P.G., A.O. and S.J. performed unsupervised sectioning of cortical samples. K.A., B.V. and S.G. contributed to data interpretation. Z.H., D.H., O.E. and P.K. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Philipp Khaitovich.

Integrated supplementary information

Supplementary information

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    Supplementary Text and Figures

    Supplementary Figures 1–12

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    Supplementary Methods Checklist

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  1. 1.

    Supplementary Table 1

    DS1 and DS2 sample information.

  2. 2.

    Supplementary Table 2

    Gene expression characteristics of the detected genes in DS1, including laminar section-related expression, layer specificity, and lineage-specific changes.

  3. 3.

    Supplementary Table 3

    Primer sequences used in the real-time qPCR; general information on the antibodies used in immunohistochemistry.

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DOI

https://doi.org/10.1038/nn.4548

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