Back

FGF overactivation underlies reduced neurogenesis in cerebellar organoid models of neurodevelopmental ciliopathy

Brunetti, L.; Wiegering, A.; Anselme, I.; Pollara, L.; Catala, M.; Antoniewski, C.; Valente, E. M.; Schneider-Maunoury, S.; Vesque, C.

2025-04-16 developmental biology
10.1101/2025.04.14.648790 bioRxiv
Show abstract

Cerebellar hypoplasia and dysplasia are hallmark features of neurodevelopmental ciliopathies such as Joubert syndrome. These disorders are caused by biallelic mutations in one of over 40 genes regulating the function of the primary cilium, a near-ubiquitous antenna-like organelle involved in signal reception and transduction. To date, the pathogenetic mechanisms linking ciliary gene dysfunction to Joubert syndrome neurodevelopmental defects are poorly understood. In this study, we generate cerebellar organoids from human induced pluripotent stem cells carrying either null mutations or patient-derived variants in RPGRIP1L, a Joubert syndrome causal gene encoding a scaffold protein crucial for ciliary function. While control organoids robustly express markers of cerebellar glutamatergic and GABAergic lineages including Purkinje cells, RPGRIP1L-deficient organoids display a consistent and severe reduction in Purkinje cell markers, along with impaired neurogenesis and increased progenitor proliferation. These defects coincide with prolonged overactivation of the FGF signaling pathway. Pharmacological inhibition of FGF signaling rescues both the proliferative/neurogenic balance and Purkinje lineage formation in RPGRIP1L-deficient organoids. Thus, our findings uncover early FGF pathway deregulation as a key driver of cerebellar differentiation defects in an in vitro model of Joubert syndrome, providing new insight into the developmental origin of cerebellar impairment in neurodevelopmental ciliopathies.

Matching journals

The top 8 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.