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      ANGIOGENES: knowledge database for protein-coding and noncoding RNA genes in endothelial cells

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          Abstract

          Increasing evidence indicates the presence of long noncoding RNAs (lncRNAs) is specific to various cell types. Although lncRNAs are speculated to be more numerous than protein-coding genes, the annotations of lncRNAs remain primitive due to the lack of well-structured schemes for their identification and description. Here, we introduce a new knowledge database “ANGIOGENES” ( http://angiogenes.uni-frankfurt.de) to allow for in silico screening of protein-coding genes and lncRNAs expressed in various types of endothelial cells, which are present in all tissues. Using the latest annotations of protein-coding genes and lncRNAs, publicly-available RNA-seq data was analyzed to identify transcripts that are expressed in endothelial cells of human, mouse and zebrafish. The analyzed data were incorporated into ANGIOGENES to provide a one-stop-shop for transcriptomics data to facilitate further biological validation. ANGIOGENES is an intuitive and easy-to-use database to allow in silico screening of expressed, enriched and/or specific endothelial transcripts under various conditions. We anticipate that ANGIOGENES serves as a starting point for functional studies to elucidate the roles of protein-coding genes and lncRNAs in angiogenesis.

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          Most cited references25

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq.

            Our understanding of the development and maintenance of tissues has been greatly aided by large-scale gene expression analysis. However, tissues are invariably complex, and expression analysis of a tissue confounds the true expression patterns of its constituent cell types. Here we describe a novel strategy to access such complex samples. Single-cell RNA-seq expression profiles were generated, and clustered to form a two-dimensional cell map onto which expression data were projected. The resulting cell map integrates three levels of organization: the whole population of cells, the functionally distinct subpopulations it contains, and the single cells themselves-all without need for known markers to classify cell types. The feasibility of the strategy was demonstrated by analyzing the transcriptomes of 85 single cells of two distinct types. We believe this strategy will enable the unbiased discovery and analysis of naturally occurring cell types during development, adult physiology, and disease.
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              Is Open Access

              Genome-wide analysis of long noncoding RNA stability

              Transcriptomic analyses have identified tens of thousands of intergenic, intronic, and cis -antisense long noncoding RNAs (lncRNAs) that are expressed from mammalian genomes. Despite progress in functional characterization, little is known about the post-transcriptional regulation of lncRNAs and their half-lives. Although many are easily detectable by a variety of techniques, it has been assumed that lncRNAs are generally unstable, but this has not been examined genome-wide. Utilizing a custom noncoding RNA array, we determined the half-lives of ∼800 lncRNAs and ∼12,000 mRNAs in the mouse Neuro-2a cell line. We find only a minority of lncRNAs are unstable. LncRNA half-lives vary over a wide range, comparable to, although on average less than, that of mRNAs, suggestive of complex metabolism and widespread functionality. Combining half-lives with comprehensive lncRNA annotations identified hundreds of unstable (half-life < 2 h) intergenic, cis -antisense, and intronic lncRNAs, as well as lncRNAs showing extreme stability (half-life > 16 h). Analysis of lncRNA features revealed that intergenic and cis -antisense RNAs are more stable than those derived from introns, as are spliced lncRNAs compared to unspliced (single exon) transcripts. Subcellular localization of lncRNAs indicated widespread trafficking to different cellular locations, with nuclear-localized lncRNAs more likely to be unstable. Surprisingly, one of the least stable lncRNAs is the well-characterized paraspeckle RNA Neat1 , suggesting Neat1 instability contributes to the dynamic nature of this subnuclear domain. We have created an online interactive resource ( http://stability.matticklab.com ) that allows easy navigation of lncRNA and mRNA stability profiles and provides a comprehensive annotation of ∼7200 mouse lncRNAs.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                01 September 2016
                2016
                : 6
                : 32475
                Affiliations
                [1 ]Institute of Cardiovascular Regeneration, Centre for Molecular Medicine, Goethe University Frankfurt , Theodor-Stern-Kai 7, Frankfurt am Main 60590, Germany
                [2 ]German Center for Cardiovascular Research, Partner side Rhein-Main , Frankfurt am Main 60590, Germany
                [3 ]THM - University of Applied Sciences, Department MNI , Wiesenstr. 14, D-35390 Giessen, Germany
                [4 ]Laboratory for Functional and Medical Genomics, Berlin Institute for Medical Systems Biology , Lindenberger Weg 80, Berlin 13125, Germany
                [5 ]German Center for Cardiovascular Research, Partner side Berlin , Berlin 13125, Germany
                [6 ]Department of Biology, South University of Science and Technology of China , 1088 Xueyuan Rd, Nanshan District, Shenzhen, Guangdong 518055, China
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep32475
                10.1038/srep32475
                5007478
                27582018
                3ee20409-a6a6-4464-a694-3d4f63cf9958
                Copyright © 2016, The Author(s)

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 23 March 2016
                : 08 August 2016
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