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      Whole-transcriptome analysis of UUO mouse model of renal fibrosis reveals new molecular players in kidney diseases

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          Abstract

          Transcriptome analysis by RNA-seq technology allows novel insights into gene expression and regulatory networks in health and disease. To better understand the molecular basis of renal fibrosis, we performed RNA-seq analysis in the Unilateral Ureteric Obstruction (UUO) mouse model. We analysed sham operated, 2- and 8-day post-ligation renal tissues. Thousands of genes with statistical significant changes in their expression were identified and classified into cellular processes and molecular pathways. Many novel protein-coding genes were identified, including critical transcription factors with important regulatory roles in other tissues and diseases. Emphasis was placed on long non-coding RNAs (lncRNAs), a class of molecular regulators of multiple and diverse cellular functions. Selected lncRNA genes were further studied and their transcriptional activity was confirmed. For three of them, their transcripts were also examined in other mouse models of nephropathies and their up- or down-regulation was found similar to the UUO model. In vitro experiments confirmed that one selected lncRNA is independent of TGFβ or IL1b stimulation but can influence the expression of fibrosis-related proteins and the cellular phenotype. These data provide new information about the involvement of protein-coding and lncRNA genes in nephropathies, which can become novel diagnostic and therapeutic targets in the near future.

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          Most cited references37

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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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            The transcriptional landscape of the mammalian genome.

            This study describes comprehensive polling of transcription start and termination sites and analysis of previously unidentified full-length complementary DNAs derived from the mouse genome. We identify the 5' and 3' boundaries of 181,047 transcripts with extensive variation in transcripts arising from alternative promoter usage, splicing, and polyadenylation. There are 16,247 new mouse protein-coding transcripts, including 5154 encoding previously unidentified proteins. Genomic mapping of the transcriptome reveals transcriptional forests, with overlapping transcription on both strands, separated by deserts in which few transcripts are observed. The data provide a comprehensive platform for the comparative analysis of mammalian transcriptional regulation in differentiation and development.
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              RNA maps reveal new RNA classes and a possible function for pervasive transcription.

              Significant fractions of eukaryotic genomes give rise to RNA, much of which is unannotated and has reduced protein-coding potential. The genomic origins and the associations of human nuclear and cytosolic polyadenylated RNAs longer than 200 nucleotides (nt) and whole-cell RNAs less than 200 nt were investigated in this genome-wide study. Subcellular addresses for nucleotides present in detected RNAs were assigned, and their potential processing into short RNAs was investigated. Taken together, these observations suggest a novel role for some unannotated RNAs as primary transcripts for the production of short RNAs. Three potentially functional classes of RNAs have been identified, two of which are syntenically conserved and correlate with the expression state of protein-coding genes. These data support a highly interleaved organization of the human transcriptome.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                18 May 2016
                2016
                : 6
                : 26235
                Affiliations
                [1 ]Center for Clinical, Experimental Surgery and Translational Research, Biomedical Research Foundation of the Academy of Athens , Athens, Greece
                [2 ]HybridStat Predictive Analytics , Athens, Greece
                [3 ]INSERM UMR-S1155, Tenon Hospital , Paris, France
                [4 ]Center for Basic Research, Biomedical Research Foundation of the Academy of Athens , Athens, Greece
                Author notes
                [*]

                These authors contributed equally to this work.

                Article
                srep26235
                10.1038/srep26235
                4870569
                27189340
                358efcce-c7c8-4956-82ff-2759375fd9ee
                Copyright © 2016, Macmillan Publishers Limited

                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
                : 18 December 2015
                : 28 April 2016
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