Direct and indirect neurogenesis generate a mosaic of distinct glutamatergic projection neuron types in cerebral cortex

Abstract

Variations in size and complexity of the cerebral cortex result from differences in neuron number and composition, which are rooted in evolutionary changes in direct and indirect neurogenesis (dNG and iNG) mediated by radial glial progenitors and intermediate progenitors, respectively. How dNG and iNG differentially contribute to cortical neuronal number, diversity, and connectivity are unknown. Establishing a genetic fate-mapping method to differentially visualize dNG and iNG in mice, we found that while both dNG and iNG contribute to all cortical structures, iNG contributes the largest relative proportions to the hippocampus and neocortex compared to insular and piriform cortex, claustrum, and the pallial amygdala. Within the neocortex, whereas dNG generates all major glutamatergic projection neuron (PN) classes, iNG differentially amplifies and diversifies PNs within each class; the two neurogenic pathways generate distinct PN types and assemble fine mosaics of lineage-based cortical subnetworks. Our results establish a ground-level lineage framework for understanding cortical development and evolution by linking foundational progenitor types and neurogenic pathways to PN types.

The characteristics of excitatory lineage differentiation and the developmental conservation in Reeler neocortex

“…Perhaps, the phenomenon is attributed to omissive apoptosis of neurons, because we validate that a quarter of neurons undergo stochastic apoptosis (Figure 3F). This is one of the reasons why the proportion of indirect neurogenesis in our lineage is higher than the result reported by Huilgol et al recently 70 . They utilized the genetic intersection–subtraction strategy to detect the proportion of neurons from direct and indirect neurogenesis at P30, and collected the neurons without apoptotic neurons.…”

“…This is one of the reasons why the proportion of indirect neurogenesis in our lineage is higher than the result reported by Huilgol et al recently. 70 They utilized the genetic intersection-subtraction strategy to detect the proportion of neurons from direct and indirect neurogenesis at P30, and collected the neurons without apoptotic neurons. Indeed, IPCs express several "dependence receptors" that induce apoptosis in the absence of ligand, such as Ntrk3, Unc5d and Epha4.…”

Combinatorial genetic strategies for dissecting cell lineages, cell types, and gene function in the mouse brain

“…Intersectional and subtractional fate mapping have been developed using the combination of two transcription factors expressed in partially overlapping patterns (He et al, 2016). This approach helps to target more restricted progenitor domains, delineate different forms of neurogenesis, and decode lineage progression from multipotent to fate‐restricted progenitors (Figure 2; Gong et al, 2022; Huilgol et al, 2023).…”

“…In another study, Cre or CreER driver targeting radial glia (RG) was combined with an intermediate progenitor (IP)‐specific Tbr2 Flp driver and an intersection‐subtraction reporter (IS) (Figure 1c) to differentially visualize direct and indirect neurogenesis (dNG and iNG) in the cortex (Figure 2c; Huilgol et al, 2023). Both forms of neurogenesis start from asymmetric division of RGs.…”

“…The strategies and examples we introduced in the previous sections mainly rely on orthogonal recombinases (Li et al, 2023) and transcriptional regulators expressed by transgenic drivers for combinatorial genetic manipulation (Gong et al, 2022). This type of combinatorial genetic targeting and manipulation has been the most commonly used so far (Fenno et al, 2020; Hafner et al, 2019; Hou et al, 2021; Huilgol et al, 2023; Kelly et al, 2018; Li et al, 2021; Poulin et al, 2018; Wu et al, 2023; Xu et al, 2022; Yetman et al, 2019). However, strategies based on viral drivers may offer unique advantages in terms of flexibility in targeting neurons with specific connectivity features (Cong et al, 2020; Liu et al, 2022; Qiu et al, 2022; Weinholtz & Castle, 2021) and provide experimental access to species that are less amenable to germline engineering (Campos et al, 2023; Juttner et al, 2019; Mehta et al, 2019; Mich et al, 2021; Vormstein‐Schneider et al, 2020).…”