Communications BiologyDevelopmental BiologyPeer-reviewed journal article
Stage-specific expression patterns and co-targeting relationships among miRNAs in the developing mouse cerebral cortex
Hristo TodoroviD, Stephan WeißbachiD, Laura Schlichtholz, Hanna Mueller, Dewi HartwichiD, Susanne GerberiD, Jennifer WinteriD
- Citations
- 15
- FWCI
- 2.80
- Field percentile
- top 8%
Abstract
microRNAs are particularly important during brain development, however, the composition and temporal dynamics of miRNA regulatory networks are not sufficiently characterized. Here, we performed small RNA sequencing of mouse embryonic cortical samples at E14, E17, and P0 as well as in neural progenitor cells differentiated in vitro into neurons. Using co-expression network analysis, we detected clusters of miRNAs that were co-regulated at distinct developmental stages. miRNAs such as miR-92a/b acted as hubs during early, and miR-124 and miR-137 during late neurogenesis. Notably, validated targets of P0 hub miRNAs were enriched for down-regulated genes related to stem cell proliferation, negative regulation of neuronal differentiation and RNA splicing, among others, suggesting that miRNAs are particularly important for modulating transcriptional programs of crucial factors that guide the switch to neuronal differentiation. As most genes contain binding sites for more than one miRNA, we furthermore constructed a co-targeting network where numerous miRNAs shared more targets than expected by chance. Using luciferase reporter assays, we demonstrated that simultaneous binding of miRNA pairs to neurodevelopmentally relevant genes exerted an enhanced transcriptional silencing effect compared to single miRNAs. Taken together, our study provides a comprehensive resource of miRNA longitudinal expression changes during corticogenesis. Furthermore, we highlight several potential mechanisms through which miRNA regulatory networks can shape embryonic brain development.
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
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