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ERK signaling integrates multiple mechanisms to drive cortical evolutionary expansion

GSE341151 Mus musculus Expression profiling by high throughput sequencing 7 samples Submitted 2026/07/28 Platform GPL24247
Summary
A critical first step in human evolutionary divergence from chimpanzees and other primates is the production of greatly increased numbers of cortical pyramidal neurons during development and over evolutionary time. This expansion underpins the enlarged human cerebral cortex and, consequently, higher-order cognition and consciousness. However, the cellular and molecular mechanisms driving this progressive increase in cortical neuron number remain incompletely understood. Here we show that elevated ERK signaling in human cortical radial glia (RGs), relative to mouse RGs, arises from evolutionary changes in the developmental expression of existing shared genes. Using the Emx1-Cre line to overexpress MEK1DD, a constitutively active mutant of rat MAP2K1, we found that enhanced ERK signaling in mouse cortical RGs upregulates cAMP–PKA signaling, along with promoting self-renewal, expanding the RG pool, and accelerating cell cycle progression. Conversely, overexpression of PKA signaling in mouse cortical RGs via in utero electroporation of constitutively active PRKACA mutants (L205R or W196G) reduces ERK activity, prolongs the cell cycle, suppresses SHH–SMO and YAP/TAZ pathway activity, and blocks ependymal gliogenesis. Together, our results demonstrate that ERK and PKA signaling in cortical RGs engage a dynamic balance of synergistic and antagonistic interactions. This interplay couples evolutionarily enhanced ERK and PKA activities to increased cortical RG numbers, prolonged cell cycle progression, and an extended neurogenic period, which collectively culminate in a marked increase in neuronal production. We conclude that heightened ERK pathway activity in cortical RGs serves as a central driver of progressive neocortical expansion across mammalian evolution.
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Also filed as BioProject PRJNA1499660 and SRA study SRP720718. Searching any of these in the dataset finder brings you back here.

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