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CRISPR-TRAPSeq identifies the QKI RNA binding protein as important for astrocytic maturation and control of thalamocortical synapses (TRAP-Seq dataset)

ABSTRACT: Quaking RNA binding protein(QKI) is essential for oligodendrocyte development as myelination requires MBP mRNA regulation and localization to distal processes by its cytoplasmic isoforms(e.g. QKI-6). QKI-6 is also highly expressed in astrocytes, which we and others recently demonstrated have regulated mRNA localization. Here, we show via CLIPseq that QKI-6 binds 3’UTRs of a subset of astrocytic mRNAs, including many enriched in peripheral processes. Binding is enriched near stop codons, which is mediated partially by QKI binding motifs(QBMs) yet spreads to adjacent sequences. We developed CRISPR TRAPseq: a viral approach for mosaic, cell-type specific gene mutation with simultaneous translational profiling. This enabled study of QKI-6 CLIP targets in QKI-deleted astrocytes in an otherwise normal brain. Astrocyte-targeted QKI deletion altered translation and maturation, while also increasing synaptic density within the astrocyte's territory. Overall, our data indicate QKI is required for astrocyte maturation and demonstrate an approach for a highly targeted translational assessment of gene knockout in specific cell-types in vivo.

ORGANISM(S): Mus musculus

PROVIDER: GSE146935 | GEO | 2021/01/21

REPOSITORIES: GEO

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Project description:MartínJiménez2017 - Genome-scale reconstruction of the human astrocyte metabolic network This model is described in the article: Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network. Martín-Jiménez CA, Salazar-Barreto D, Barreto GE, González J. Front Aging Neurosci 2017; 9: 23 Abstract: Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework to elucidate how astrocytes modulate human brain metabolic states during normal conditions and in neurodegenerative diseases. We performed a Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network with the purpose of elucidating a significant portion of the metabolic map of the astrocyte. This is the first global high-quality, manually curated metabolic reconstruction network of a human astrocyte. It includes 5,007 metabolites and 5,659 reactions distributed among 8 cell compartments, (extracellular, cytoplasm, mitochondria, endoplasmic reticle, Golgi apparatus, lysosome, peroxisome and nucleus). Using the reconstructed network, the metabolic capabilities of human astrocytes were calculated and compared both in normal and ischemic conditions. We identified reactions activated in these two states, which can be useful for understanding the astrocytic pathways that are affected during brain disease. Additionally, we also showed that the obtained flux distributions in the model, are in accordance with literature-based findings. Up to date, this is the most complete representation of the human astrocyte in terms of inclusion of genes, proteins, reactions and metabolic pathways, being a useful guide for in-silico analysis of several metabolic behaviors of the astrocyte during normal and pathologic states. This model is hosted on BioModels Database and identified by: MODEL1608180000. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

Dataset Information

CRISPR-TRAPSeq identifies the QKI RNA binding protein as important for astrocytic maturation and control of thalamocortical synapses (TRAP-Seq dataset)

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