Single-cell spatial transcriptome reveals cell-type organization in the macaque cortex
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Abstract
Elucidating the cellular organization of the cerebral cortex is critical for understanding brain structure and function. Using large-scale single-nucleus RNA sequencing and spatial transcriptomic analysis of 143 macaque cortical regions, we obtained a comprehensive atlas of 264 transcriptome-defined cortical cell types and mapped their spatial distribution across the entire cortex. We characterized the cortical layer and region preferences of glutamatergic, GABAergic, and non-neuronal cell types, as well as regional differences in cell-type composition and neighborhood complexity. Notably, we discovered a relationship between the regional distribution of various cell types and the region's hierarchical level in the visual and somatosensory systems. Cross-species comparison of transcriptomic data from human, macaque, and mouse cortices further revealed primate-specific cell types that are enriched in layer 4, with their marker genes expressed in a region-dependent manner. Our data provide a cellular and molecular basis for understanding the evolution, development, aging, and pathogenesis of the primate brain.
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Self-citationCytoarchitectonic and connection stripes in the dysgranular insular cortex in the macaque monkey
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High-robustness autofocusing method in the microscope with laser-based arrayed spots
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Self-citationIdentification and application of cell-type-specific enhancers for the macaque brain
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Self-citationInterpretable niche-based cell‒cell communication inference using multi-view graph neural networks
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Kim, J. Y., Poddar, A., Sandoval, K., Chu, J. S. F., Horton, E. C., Cui, D., Nakamura, K. C., Lu, I.-L., Mui, M. H., Bartels, T., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01987-2 · Cited by 11 · see citing works
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Spatial Transcriptomics: Biotechnologies, Computational Tools, and Neuroscience Applications
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Self-citationSpatial-Omics Methods and Applications
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Machine learning identification of enhancers in the rhesus macaque genome
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Self-citationAging imaging: the future demand of health management
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Self-citationMAPbrain: a multi-omics atlas of the primate brain
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Self-citationTranscriptional Cartography Integrates Multiscale Biology of the Human CortexPreprint
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Self-citationInsights into Neurodegeneration in Parkinson's Disease from Single‐Cell and Spatial Genomics
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Self-citationSpatially resolved mapping of cells associated with human complex traitsPreprint
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Self-citationSCAN: Spatiotemporal Cloud Atlas for Neural cells
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Self-citationGenomic evolution reshapes cell-type diversification in the amniote brain
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Self-citationSpatially resolved molecular and cellular atlas of the mouse brainPreprint
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Self-citationSpatial Transcriptomic Alignment, Integration, and de novo 3D Reconstruction by STAIRPreprint
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Microglial states associate with lesion dynamics in multiple sclerosis
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An opposing molecular gradient axis underlies primate cortical organization
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Self-citationWhy non-human primates are needed in stroke preclinical research
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Distribution of calbindin-positive neurons across areas and layers of the marmoset cerebral cortex
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NeMO Analytics: a compendium of transcriptomic data for the exploration of neocortical development
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BrainBeacon: A Cross-Species Foundation Model for Single-cell Resolved Brain Spatial TranscriptomicsPreprint
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Mesoscopic mapping of the brain: From rodents to primates
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Self-citationCo-Conservation of synaptic gene expression and circuitry in collicular neurons
Liu, Y., McDaniel, J. A., Chen, C., Yang, L., Kıpçak, A., Savier, E. L., Erişir, A., Cang, J., & Campbell, J. N. (2025) · Nature Communications · doi:10.1038/s41467-025-64204-5 · Cited by 5 · see citing works
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Self-citationCompetitive interactions shape mammalian brain network dynamics and computation
Luppi, A. I., Perl, Y. S., Vohryzek, J., Ali, H., Mediano, P. A. M., Rosas, F. E., Milisav, F., Suárez, L. E., Gini, S., Gutierrez‐Barragan, D., et al. (2026) · Nature Neuroscience · doi:10.1038/s41593-026-02205-3 · Cited by 5 · see citing works
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Self-citation
- Authors
- Chen, A., Sun, Y., Lei, Y., Li, C., Liao, S., Meng, J., Bai, Y., Liu, Z., Liang, Z., Zhu, Z., Yuan, N., Yang, H., Wu, Z., Lin, F., Wang, K., Li, M., Zhang, S., Yang, M., Fei, T., Zhuang, Z., Huang, Y., Zhang, Y., Xu, Y., Cui, L., Zhang, R., Han, L., Sun, X., Chen, B., Li, W., Huangfu, B., Ma, K., Ma, J., Li, Z., Lin, Y., Wang, H., Zhong, Y., Zhang, H., Yu, Q., Wang, Y., Liu, X., Peng, J., Liu, C., Chen, W., Pan, W., An, Y., Xia, S., Lu, Y., Wang, M., Song, X., Liu, S., Wang, Z., Gong, C., Huang, X., Yuan, Y., Zhao, Y., Chai, Q., Tan, X., Liu, J., Zheng, M., Li, S., Huang, Y., Hong, Y., Huang, Z., Li, M., Jin, M., Li, Y., Zhang, H., Sun, S., Gao, L., Bai, Y., Cheng, M., Hu, G., Liu, S., Wang, B., Xiang, B., Li, S., Li, H., Chen, M., Wang, S., Li, M., Liu, W., Liu, X., Zhao, Q., Lisby, M., Wang, J., Fang, J., Lin, Y., Xie, Q., Liu, Z., He, J., Xu, H., Huang, W., Mulder, J., Yang, H., Sun, Y., Uhlen, M., Poo, M., Wang, J., Yao, J., Wei, W., Li, Y., Shen, Z., Liu, L., Liu, Z., Xu, X., & Li, C.
- Affiliations
- BGI Group (China) (CN)
- Center for Excellence in Brain Science and Intelligence Technology (CN)
- Tencent (China) (CN)
- Shanghai Institute of Nutrition and Health (CN)
- China National GeneBank (CN)
- University of Copenhagen (DK)
- Science for Life Laboratory (SE)
- Chinese Academy of Sciences (CN)
- Corresponding author
- Sun, Yidi
- Yao, Jianhua
- Li, Yuxiang
- Shen, Zhiming
- Liu, Longqi
- Liu, Zhiyong
- Xu, Xun
- Li, Chengyu
- ORCID
- Chen, Ao
- Sun, Yidi
- Lei, Ying
- Li, Chao
- Liao, Sha
- Meng, Juan
- Bai, Yiqin
- Yang, Hao
- Wu, Zihan
- Lin, Feng
- Wang, Kexin
- Li, Mei
- Fei, Tianyi
- Zhuang, Zhenkun
- Huang, Yiming
- Zhang, Yong
- Zhang, Ruiyi
- Han, Lei
- Sun, Xing
- Chen, Bichao
- Li, Wenjiao
- Ma, Kailong
- Wang, He
- Zhang, Huifang
- Wang, Yaqian
- Liu, Xing
- Peng, Jian
- Liu, Chuanyu
- Chen, Wei
- Pan, Wentao
- Xia, Shihui
- Wang, Mingli
- Song, Xinxiang
- Wang, Zhifeng
- Huang, Xin
- Yuan, Yue
- Zhao, Yun
- Chai, Qinwen
- Tan, Xing
- Li, Shengkang
- Huang, Yaling
- Li, Min
- Jin, Mengmeng
- Li, Yan
- Zhang, Hui
- Sun, Suhong
- Gao, Li
- Bai, Yinqi
- Hu, Guohai
- Liu, Shiping
- Wang, Bo
- Li, Huanhuan
- Chen, Mengni
- Wang, Shiwen
- Li, Minglong
- Liu, Weibin
- Liu, Xin
- Zhao, Qian
- Lisby, Michael
- Wang, Jing
- Xie, Qing
- He, Jie
- Xu, Huatai
- Huang, Wei
- Mulder, Jan
- Yang, Huanming
- Wang, Jian
- Yao, Jianhua
- Wei, Wu
- Li, Yuxiang
- Shen, Zhiming
- Liu, Longqi
- Liu, Zhiyong
- Xu, Xun
- Li, Chengyu
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2023-08
- Volume
- 186
- Issue
- 17
- Pages
- 3726-3743.e24
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W4384071384
- Cited by
- 232
- References
- 122
- Citations by year
- 2026: 57 · 2025: 81 · 2024: 65 · 2023: 26 · 2022: 3
- FWCI
- 20.41
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, cc-by)
- Funders
- National Natural Science Foundation of China (2018SHZDZX05, 31827803, 31900466)
- Chinese Academy of Sciences (153D31KYSB20170059, 2018SHZDZX05, XDB32010100)
- Shenzhen Fundamental Research Program
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- macaque cortex, cortical cell types, single-nucleus RNA sequencing, spatial transcriptomics, cell type atlas, cortical layers, cortical regions, glutamatergic neurons, GABAergic neurons, non-neuronal cells, layer 4, cross-species comparison, primate brain evolution
- MeSH terms
- Animals, Cerebral Cortex, Humans, Macaca, Mice, Single-Cell Analysis, Transcriptome
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