bioRxivNeurosciencePreprint
Molecular mechanisms driving divergent development of the human frontal and visual cortex during prenatal development
Gabriela EpihovaiD, Dimitar Z. EpihoviD, Danyal AkarcaiD, Duncan Edward AstleiD
Abstract
Key principles of structural brain organization are established very early in fetal development. The frontal cortex is an important hub for integration and control of information, and its integrity and connectivity within the wider neural system are linked to individual differences across multiple cognitive domains and neurodevelopmental conditions. Here we leveraged fetal brain transcriptomics to investigate molecular mechanisms during prenatal development that drive early differences between the two regions at the opposite poles of the physical and representational gradient of the brain - the frontal and visual cortex. We show that the frontal cortex exhibits significantly higher cumulative gene expression for pathways involved in the continued growth and maintenance of larger neurons. These pathways include the gene ontology terms of neuron development and neuronal cell body as well as glucose metabolism important in trophically supporting larger cell sizes. Whole pathways for axonal growth (axonal growth cone, microtubules, filopodia, lamellipodia) and single genes involved in circuit connectivity exhibited increased expression in the frontal cortex. In contrast, in line with the established earlier completion of neurogenesis and lower number of neurons in the anterior cortex, expression of genes involved in DNA replication was significantly lower relative to the visual cortex. We further demonstrate differential cellular composition with higher expression of marker genes for inhibitory neurons in the prenatal frontal cortex. Together, these results suggest that the cellular architecture and composition facilitates earlier connectivity in the frontal cortex which may determine its role as an integrative hub in the global brain organization.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 1
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