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Making sense of mRNA landscapes: Translation control in neurodevelopment

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Abstract Like all other parts of the central nervous system, the mammalian neocortex undergoes temporally ordered set of developmental events, including proliferation, differentiation, migration, cellular identity, synaptogenesis, connectivity formation, and plasticity changes. These neurodevelopmental mechanisms have been characterized by studies focused on transcriptional control. Recent findings, however, have shown that the spatiotemporal regulation of post‐transcriptional steps like alternative splicing, mRNA traffic/localization, mRNA stability/decay, and finally repression/derepression of protein synthesis (mRNA translation) have become just as central to the neurodevelopment as transcriptional control. A number of dynamic players act post‐transcriptionally in the neocortex to regulate these steps, as RNA binding proteins (RBPs), ribosomal proteins (RPs), long non‐coding RNAs, and/or microRNA. Remarkably, mutations in these post‐transcriptional regulators have been associated with neurodevelopmental, neurodegenerative, inherited, or often co‐morbid disorders, such as microcephaly, autism, epilepsy, intellectual disability, white matter diseases, Rett‐syndrome like phenotype, spinocerebellar ataxia, and amyotrophic lateral sclerosis. Here, we focus on the current state, advanced methodologies and pitfalls of this exciting and upcoming field of RNA metabolism with vast potential in understanding fundamental neurodevelopmental processes and pathologies. This article is categorized under: Translation > Translation Regulation RNA in Disease and Development > RNA in Disease RNA Interactions with Proteins and Other Molecules > Protein‐RNA Interactions: Functional Implications
RNA metabolism. (a) Life of an RNA from transcription, splicing export, and transport to degradation, deadenylation, storage/silencing, or ultimately to mRNA translation (protein synthesis). All steps of RNA life are regulated by RNA binding proteins (RBPs). (b) Neocortical development undergoes distinct steps that are tightly regulated at transcriptional and post‐transcriptional level. RBPs were found to play role in most of the developmental steps, such as proliferation and fate acquisition, migration, axon growth, differentiation, connectivity, plasticity, and cell maintenance. Legend is on the right. For more details please see text
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Cell‐type specific RBPs in the developing neocortex. (a,c) single‐cell RNA‐seq data of the mouse developing neocortex at E14.5 (a) and P0 (c) were taken from Loo et al., 2019 (GSE120046) and dimensionality reduction UMAP plots were generated after filtering for cell‐types of interest (left). Cells are clustered based on their similarities in gene expression. Cells were annotated according to original classifications provided by Loo et al., 2019 and then the proportion of expression for each gene attributed to each cell‐type was calculated using functions from Skene & Grant, 2016 and defined as a “specificity score” from 0.25 to 1. A specificity score of 0.25 indicates that gene expression is equally proportional across all cell‐types while a specificity score of 1 indicates exclusive expression in one cell‐type. The top three RBPs for each cell‐type and their corresponding specificity score are shown (right). For IPCs at E14.5, no RBP was observed with a specificity score >0.5. (b, d) All genes ordered by their maximum specificity score are plotted along the x‐axis and the probability density of RBPs or TFs in this ordered list are shown (b: E14.5; d: P0). Across developmental ages, the list of the most highly cell‐type specific genes are dominated by TFs. Vertical dotted lines represent the mean specificity score rank among TFs and RBPs. (e) Violin plots of maximum specificity scores across RBPs and TFs at P0 demonstrate that difficulties detecting cell‐type specific RBPs are not due to difficulties detecting cell‐type specific genes in general. Canonical cell‐type specific TFs are labeled as an example. (f, g) E14.5 UMAP plots of putative RG specific RBPs, Zfp36l1 (f), and Zfp36l2 (g). Black dotted line indicates RG specific cluster. R code used to perform this analysis is publicly available at: https://github.com/np519/WIREs_RNA_Review_2020. UMAP, Uniform manifold approximation and projection; RG, radial glia; ExN, excitatory neurons; InN, inhibitory neurons; IPC, intermediate progenitor cells; Astro, astrocytes; Oligo, oligodendrocytes; EWCE, expression weighted cell‐type enrichment; RBP, RNA‐binding protein; TF, Transcription factor. RBPs were defined by the list of genes included in the GO term “RNA binding” (ID = GO:0003723) as accessed on July 22, 2020 (http://www.informatics.jax.org/go/term/GO:0003723). The evidence codes for the majority of RBPs examined included IDA, IEA, and ISO which means that annotations were either “inferred from direct assay,” “inferred from electronic annotation,” or “inferred from sequence orthologs” (http://www.informatics.jax.org/function.shtml). A total of 928 unique RBPs were examined
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RNA Interactions with Proteins and Other Molecules > Protein–RNA Interactions: Functional Implications
RNA in Disease and Development > RNA in Disease
Translation > Translation Regulation

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