Spatial transcriptomics reveals human cortical layer and area specification.
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Abstract | The human cerebral cortex is composed of six layers and dozens of areas that are molecularly and structurally distinct. Although single-cell transcriptomic studies have advanced the molecular characterization of human cortical development, a substantial gap exists owing to the loss of spatial context during cell dissociation. Here we used multiplexed error-robust fluorescence in situ hybridization (MERFISH), augmented with deep-learning-based nucleus segmentation, to examine the molecular, cellular and cytoarchitectural development of the human fetal cortex with spatially resolved single-cell resolution. Our extensive spatial atlas, encompassing more than 18 million single cells, spans eight cortical areas across seven developmental time points. We uncovered the early establishment of the six-layer structure, identifiable by the laminar distribution of excitatory neuron subtypes, 3 months before the emergence of cytoarchitectural layers. Notably, we discovered two distinct modes of cortical areal specification during mid-gestation: (1) a continuous, gradual transition observed across most cortical areas along the anterior-posterior axis and (2) a discrete, abrupt boundary specifically identified between the primary (V1) and secondary (V2) visual cortices as early as gestational week 20. This sharp binary transition in V1-V2 neuronal subtypes challenges the notion that mid-gestation cortical arealization involves only gradient-like transitions. Furthermore, integrating single-nucleus RNA sequencing with MERFISH revealed an early upregulation of synaptogenesis in V1-specific layer 4 neurons. Collectively, our findings underscore the crucial role of spatial relationships in determining the molecular specification of cortical layers and areas. This study establishes a spatially resolved single-cell analysis paradigm and paves the way for the construction of a comprehensive developmental atlas of the human brain. |
Year of Publication | 2025
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Journal | Nature
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Volume | 644
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Issue | 8075
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Pages | 153-163
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Date Published | 08/2025
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ISSN | 1476-4687
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DOI | 10.1038/s41586-025-09010-1
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PubMed ID | 40369074
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