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1000 Titel
  • Polymorphisms in miRNA binding sites involved in metabolic diseases in mice and humans
1000 Autor/in
  1. Gottmann, Pascal |
  2. Ouni, Meriem |
  3. Zellner, Lisa |
  4. Jähnert, Markus |
  5. Rittig, Kilian |
  6. Walther, Dirk |
  7. Schürmann, Annette |
1000 Erscheinungsjahr 2020
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-04-29
1000 Erschienen in
1000 Quellenangabe
  • 10(1):7202
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1038/s41598-020-64326-4 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190857/ |
1000 Ergänzendes Material
  • https://www.nature.com/articles/s41598-020-64326-4#Sec24 |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Type 2 diabetes and obesity are well-studied metabolic diseases, which are based on genetic and epigenetic alterations in combination with an obesogenic lifestyle. The aim of this study was to test whether SNPs in miRNA-mRNA binding sites that potentially disrupt binding, elevate the expression of miRNA targets, which participate in the development of metabolic diseases. A computational approach was developed that integrates transcriptomics, linkage analysis, miRNA-target prediction data, and sequence information of a mouse model of obesity and diabetes. A statistical analysis demonstrated a significant enrichment of 566 genes for a location in obesity- and diabetes-related QTL. They are expressed at higher levels in metabolically relevant tissues presumably due to altered miRNA-mRNA binding sites. Of these, 51 genes harbor conserved and impaired miRNA-mRNA-interactions in human. Among these, 38 genes have been associated to metabolic diseases according to the phenotypes of corresponding knockout mice or other results described in the literature. The remaining 13 genes (e.g. Jrk, Megf9, Slfn8 and Tmem132e) could be interesting candidates and will be investigated in the future.
1000 Sacherschließung
lokal Obesity
lokal Type 2 diabetes
lokal Computational biology and bioinformatics
lokal miRNAs
lokal Data mining
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://frl.publisso.de/adhoc/uri/R290dG1hbm4sIFBhc2NhbA==|https://frl.publisso.de/adhoc/uri/T3VuaSwgTWVyaWVt|https://frl.publisso.de/adhoc/uri/WmVsbG5lciwgTGlzYQ==|https://frl.publisso.de/adhoc/uri/SsOkaG5lcnQsIE1hcmt1cw==|https://frl.publisso.de/adhoc/uri/Uml0dGlnLCBLaWxpYW4=|https://frl.publisso.de/adhoc/uri/V2FsdGhlciwgRGlyaw==|https://frl.publisso.de/adhoc/uri/U2Now7xybWFubiwgQW5uZXR0ZQ==
1000 Label
1000 Förderer
  1. Bundesministerium für Bildung und Forschung |
  2. Brandenburg state |
1000 Fördernummer
  1. -
  2. 82DZD00302
1000 Förderprogramm
  1. -
  2. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Bundesministerium für Bildung und Forschung |
    1000 Förderprogramm -
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer Brandenburg state |
    1000 Förderprogramm -
    1000 Fördernummer 82DZD00302
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6426892.rdf
1000 Erstellt am 2021-04-16T12:55:00.432+0200
1000 Erstellt von 25
1000 beschreibt frl:6426892
1000 Bearbeitet von 25
1000 Zuletzt bearbeitet 2021-04-16T12:56:04.485+0200
1000 Objekt bearb. Fri Apr 16 12:55:44 CEST 2021
1000 Vgl. frl:6426892
1000 Oai Id
  1. oai:frl.publisso.de:frl:6426892 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
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