Letter | Published:

A single-cell RNA-seq survey of the developmental landscape of the human prefrontal cortex

Nature volume 555, pages 524528 (22 March 2018) | Download Citation

Abstract

The mammalian prefrontal cortex comprises a set of highly specialized brain areas containing billions of cells and serves as the centre of the highest-order cognitive functions, such as memory, cognitive ability, decision-making and social behaviour1,2. Although neural circuits are formed in the late stages of human embryonic development and even after birth, diverse classes of functional cells are generated and migrate to the appropriate locations earlier in development. Dysfunction of the prefrontal cortex contributes to cognitive deficits and the majority of neurodevelopmental disorders; there is therefore a need for detailed knowledge of the development of the prefrontal cortex. However, it is still difficult to identify cell types in the developing human prefrontal cortex and to distinguish their developmental features. Here we analyse more than 2,300 single cells in the developing human prefrontal cortex from gestational weeks 8 to 26 using RNA sequencing. We identify 35 subtypes of cells in six main classes and trace the developmental trajectories of these cells. Detailed analysis of neural progenitor cells highlights new marker genes and unique developmental features of intermediate progenitor cells. We also map the timeline of neurogenesis of excitatory neurons in the prefrontal cortex and detect the presence of interneuron progenitors in early developing prefrontal cortex. Moreover, we reveal the intrinsic development-dependent signals that regulate neuron generation and circuit formation using single-cell transcriptomic data analysis. Our screening and characterization approach provides a blueprint for understanding the development of the human prefrontal cortex in the early and mid-gestational stages in order to systematically dissect the cellular basis and molecular regulation of prefrontal cortex function in humans.

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Acknowledgements

We thank members of the Wang and Tang laboratories for discussions. This work was supported by National Basic Research Program of China (2014CB964600), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA16020601), the National Natural Science Foundation of China (NSFC) (91732301, 31371100, 31771140), National Key Research and Development Program of China (2017YFA0103303, 2017YFA0102601), Shanghai Brain-Intelligence Project from STCSM (16JC1420500), Newton Advanced Fellowship (NA140246) to X.W. and Youth Innovation Promotion Association CAS to Q.W.

Author information

Author notes

    • Suijuan Zhong
    • , Shu Zhang
    • , Xiaoying Fan
    • , Qian Wu
    •  & Liying Yan

    These authors contributed equally to this work.

Affiliations

  1. State Key Laboratory of Brain and Cognitive Science, CAS Center for Excellence in Brain Science and Intelligence Technology (Shanghai), Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China

    • Suijuan Zhong
    • , Qian Wu
    • , Long Li
    • , Le Sun
    • , Na Pan
    •  & Xiaoqun Wang
  2. University of Chinese Academy of Sciences, Beijing, 100049, China

    • Suijuan Zhong
    • , Qian Wu
    • , Long Li
    •  & Xiaoqun Wang
  3. Beijing Advanced Innovation Center for Genomics, College of Life Sciences, Department of Obstetrics and Gynecology, Third Hospital, Peking University, Beijing, 100871, China

    • Shu Zhang
    • , Xiaoying Fan
    • , Liying Yan
    • , Ji Dong
    • , Fuchou Tang
    •  & Jie Qiao
  4. Obstetrics and Gynecology, Medical Center of Severe Cardiovascular of Beijing Anzhen Hospital, Capital Medical University, Beijing, 100029, China

    • Haofeng Zhang
    • , Xiaohui Xu
    •  & Jun Zhang
  5. Biomedical Institute for Pioneering Investigation via Convergence and Center for Reproductive Medicine, Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing, 100871, China

    • Fuchou Tang
    •  & Jie Qiao
  6. Peking–Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China

    • Fuchou Tang
    •  & Jie Qiao
  7. Beijing Institute for Brain Disorders, Beijing, 100069, China.

    • Xiaoqun Wang

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Contributions

Q.W., X.F., J.Q., F.T. and X.W. conceived the project, designed the experiments and wrote the manuscript. S.Zho. and X.F. performed RNA-seq. S.Zha. and J.D. analysed the data. J.Z., L.L., L.S., H.Z., L.Y. and X.X. prepared the samples. S.Zho. and Q.W. performed immunofluorescence, in situ hybridization and imaging. L.S. and N.P. performed the electrophysiology experiments. All authors edited and proofread the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Fuchou Tang or Jun Zhang or Jie Qiao or Xiaoqun Wang.

Reviewer Information Nature thanks H. Song and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Supplementary information

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    Life Sciences Reporting Summary

Excel files

  1. 1.

    Supplementary Table

    This file contains supplementary table 1 - gene list of different cells types and comparison. The spreadsheets include marker genes of all 6 major cell types, specific genes of the sub-clusters within each cell type, excitatory neuron markers of different weeks and gestational stages.

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DOI

https://doi.org/10.1038/nature25980

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