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      A Functional Dissection of the mRNA and Locally Synthesized Protein Population in Neuronal Dendrites and Axons

      1 , 1 , 1
      Annual Review of Genetics
      Annual Reviews

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          Abstract

          Neurons are characterized by a complex morphology that enables the generation of subcellular compartments with unique biochemical and biophysical properties, such as dendrites, axons, and synapses. To sustain these different compartments and carry a wide array of elaborate operations, neurons express a diverse repertoire of gene products. Extensive regulation at both the messenger RNA (mRNA) and protein levels allows for the differentiation of subcellular compartments as well as numerous forms of plasticity in response to variable stimuli. Among the multiple mechanisms that control cellular functions, mRNA translation is manipulated by neurons to regulate where and when a protein emerges. Interestingly, transcriptomic and translatomic profiles of both dendrites and axons have revealed that the mRNA population only partially predicts the local protein population and that this relation significantly varies between different gene groups. Here, we describe the space that local translation occupies within the large molecular and regulatory complexity of neurons, in contrast to other modes of regulation. We then discuss the specialized organization of mRNAs within different neuronal compartments, as revealed by profiles of the local transcriptome. Finally, we discuss the features and functional implications of both locally correlated—and anticorrelated—mRNA-protein relations both under baseline conditions and during synaptic plasticity.

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          Proteomics. Tissue-based map of the human proteome.

          Resolving the molecular details of proteome variation in the different tissues and organs of the human body will greatly increase our knowledge of human biology and disease. Here, we present a map of the human tissue proteome based on an integrated omics approach that involves quantitative transcriptomics at the tissue and organ level, combined with tissue microarray-based immunohistochemistry, to achieve spatial localization of proteins down to the single-cell level. Our tissue-based analysis detected more than 90% of the putative protein-coding genes. We used this approach to explore the human secretome, the membrane proteome, the druggable proteome, the cancer proteome, and the metabolic functions in 32 different tissues and organs. All the data are integrated in an interactive Web-based database that allows exploration of individual proteins, as well as navigation of global expression patterns, in all major tissues and organs in the human body. Copyright © 2015, American Association for the Advancement of Science.
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            An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex.

            The major cell classes of the brain differ in their developmental processes, metabolism, signaling, and function. To better understand the functions and interactions of the cell types that comprise these classes, we acutely purified representative populations of neurons, astrocytes, oligodendrocyte precursor cells, newly formed oligodendrocytes, myelinating oligodendrocytes, microglia, endothelial cells, and pericytes from mouse cerebral cortex. We generated a transcriptome database for these eight cell types by RNA sequencing and used a sensitive algorithm to detect alternative splicing events in each cell type. Bioinformatic analyses identified thousands of new cell type-enriched genes and splicing isoforms that will provide novel markers for cell identification, tools for genetic manipulation, and insights into the biology of the brain. For example, our data provide clues as to how neurons and astrocytes differ in their ability to dynamically regulate glycolytic flux and lactate generation attributable to unique splicing of PKM2, the gene encoding the glycolytic enzyme pyruvate kinase. This dataset will provide a powerful new resource for understanding the development and function of the brain. To ensure the widespread distribution of these datasets, we have created a user-friendly website (http://web.stanford.edu/group/barres_lab/brain_rnaseq.html) that provides a platform for analyzing and comparing transciption and alternative splicing profiles for various cell classes in the brain. Copyright © 2014 the authors 0270-6474/14/3411929-19$15.00/0.
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              Genome-wide atlas of gene expression in the adult mouse brain.

              Molecular approaches to understanding the functional circuitry of the nervous system promise new insights into the relationship between genes, brain and behaviour. The cellular diversity of the brain necessitates a cellular resolution approach towards understanding the functional genomics of the nervous system. We describe here an anatomically comprehensive digital atlas containing the expression patterns of approximately 20,000 genes in the adult mouse brain. Data were generated using automated high-throughput procedures for in situ hybridization and data acquisition, and are publicly accessible online. Newly developed image-based informatics tools allow global genome-scale structural analysis and cross-correlation, as well as identification of regionally enriched genes. Unbiased fine-resolution analysis has identified highly specific cellular markers as well as extensive evidence of cellular heterogeneity not evident in classical neuroanatomical atlases. This highly standardized atlas provides an open, primary data resource for a wide variety of further studies concerning brain organization and function.
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                Author and article information

                Journal
                Annual Review of Genetics
                Annu. Rev. Genet.
                Annual Reviews
                0066-4197
                1545-2948
                November 23 2021
                November 23 2021
                : 55
                : 1
                : 183-207
                Affiliations
                [1 ]Max Planck Institute for Brain Research, 60438 Frankfurt, Germany;
                Article
                10.1146/annurev-genet-030321-054851
                34460296
                73c76909-8913-4dd8-a1bf-04d978cb5151
                © 2021
                History

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