Mosaic Analysis with Double Markers reveals IGF1R function in granule cell progenitors during cerebellar development

利用双标记进行嵌合分析揭示了IGF1R在小脑发育过程中颗粒细胞祖细胞中的功能

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作者:Tiffany T Terry,Tao Cheng,Moe Mahjoub,Hui Zong

Abstract

During cerebellar development, granule cell progenitors (GCPs) proliferate exponentially for a fixed period, promoted by paracrine mitogenic factor Sonic Hedgehog (Shh) secreted from Purkinje cells (PCs). Dysregulation of Shh signaling leads to uncontrolled GCP proliferation and medulloblastoma. Serendipitously our previous work discovered insulin-like growth factor 1 (IGF1) as another key driver for medulloblastoma, which led to the current investigation into the role of IGF1 in GCPs during normal development. While the IGF1R conditional knockout model revealed GCP defects in anterior cerebellum, the posterior cerebellum was mostly intact, likely owing to incomplete excision of floxed alleles. To circumvent this hurdle, we enlisted a mouse genetic system called Mosaic Analysis of Double Markers (MADM), which sporadically generates homozygous null cells unequivocally labeled with GFP and their wildtype sibling cells labeled with RFP, enabling phenotypic analysis at single-cell resolution. Using MADM, we found that loss of IGF1R resulted in a 10-fold reduction of GCs in both anterior and posterior cerebellum; and that hindered S phase entry and increased cell cycle exit collectively led to this phenotype. Genetic interaction studies showed that IGF1 signaling prevents GCP cell cycle exit at least partially through suppressing the level of p27kip1, a negative regulator of cell cycle. Finally, we found that IGF1 is produced by PCs in a temporally regulated fashion: it is highly expressed early in development when GCPs proliferate exponentially, then gradually decline as GCPs commit to cell cycle exit. Taken together, our studies reveal IGF1 as a paracrine factor that positively regulates GCP cell cycle in cooperation with Shh, through dampening the level of p27 to prevent precocious cell cycle exit. Our work not only showcases the power of phenotypic analysis by the MADM system but also provides an excellent example of multi-factorial regulation of robust developmental programs.

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