Back

Uncoupling Neocortical Neuron Fate and Migration via a Let-7-RBX2 Axis

Decker, S. C.; Hino, K.; La Torre, A.; Simo, S.

2025-09-16 developmental biology
10.1101/2025.09.11.675676 bioRxiv
Show abstract

Throughout the central nervous system, the fate and migration of projection neurons are tightly coordinated to ensure that specific neuronal fates settle in precise spatial locations. This is particularly evident in the mammalian neocortex, where early-born projection neurons predominantly remain in the deeper layers of the cortical plate, whereas later-born neurons localize more superficially. However, it remains unclear whether neuronal fate acquisition directly primes the molecular mechanisms driving pyramidal neuron migration and positioning, or on the contrary fate and positioning are regulated independently. MicroRNAs have emerged as key regulators of cell fate determination in the neocortex. Among them, let-7 is known to influence neural progenitor competence and promote the neurogenesis of late-born projection neurons. Here, we show that let-7 also regulates projection neuron migration and positioning by targeting RBX2, a core component of the E3 ubiquitin ligase CRL5, which has been previously shown to inhibit neuron migration by terminating the Reelin/DAB1 signaling pathway. Let-7 directly binds to a conserved motif in the 3' UTR of RBX2, reducing its translation and thereby diminishing CRL5 activity. Importantly, restoring RBX2 levels in the context of let-7 overexpression rescues the positioning of pyramidal neurons without altering let-7-induced effects on neuronal fate. Furthermore, we demonstrate that let-7 enhances pyramidal neuron migration by increasing locomotion speed and prolonging migratory activity. Together, these findings reveal that let-7 coordinates neuronal fate specification and migration via distinct molecular pathways, ensuring the proper laminar positioning of late-born pyramidal neurons in the neocortex.

Published in Proceedings of the National Academy of Sciences (predicted rank #3) · training set

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.