bioRxivNeurosciencePreprint
Molecular and Cellular Underpinnings of Spatial Heterogeneity in Fetal Cortical Folding
Xinyi XuiD, Ruike CheniD, Tianshu ZhengiD, Zhiyong ZhaoiD, Mingyang LiiD, Dan WuiD
Abstract
Cortical folding is a defining feature of human brain development, yet the molecular and cellular mechanisms that produce regionally specific cortical folding remain incompletely understood. Here we combined high-resolution in-utero T2-weighted and diffusion MRI atlases (23-38 weeks of gestational age) with prenatal transcriptomic profiles to map regional macrostructural and microstructural features of cortical folding to underlying gene expression. We found genes whose expression patterns correlated with cortical curvature were enriched for neurogenesis, progenitor proliferation and radial glia guided neuronal migration, and localized to ventricular zone/subventricular zone progenitor cell subtypes, supporting for the protomap hypothesis of areal specification. By contrast, cortical microstructural markers-associated gene sets were implicated in myelination, cell adhesion and extracellular matrix remodeling, and mapped to astrocyte and endothelial cell programs. The microstructure-related gene expression peaked in the early postnatal period and remained high throughout childhood, while the curvature-associated gene expression reduced with age. Several of these cortical folding-related genes overlapped with autism spectrum disorder risk loci (e.g., SCN2A, STXBP1, DVL3). Collectively, these cross-modal findings outline a sequential developmental architecture--early progenitor driven patterning followed by myelin and extracellular matrix consolidation. In addition, we released a high-resolution fetal labeling atlas to facilitate further imaging-genetic studies of early cortical development.
- organism: human
- assay: spatial transcriptomics
- assay: bulk RNA-seq
- assay: imaging
- research focus: cell type annotation
- research focus: gene regulatory network inference
- research focus: database / resource
- approach: statistical model
- approach: benchmark study
- Citations
- 0
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