Please use this identifier to cite or link to this item: doi:10.22028/D291-30344
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Title: Large-scale validation of miRNAs by disease association, evolutionary conservation and pathway activity
Author(s): Fehlmann, Tobias
Laufer, Thomas
Backes, Christina
Kahramann, Mustafa
Alles, Julia
Fischer, Ulrike
Minet, Marie
Ludwig, Nicole
Kern, Fabian
Kehl, Tim
Galata, Valentina
Düsterloh, Aneta
Schrörs, Hannah
Kohlhaas, Jochen
Bals, Robert
Huwer, Hanno
Geffers, Lars
Krüger, Rejko
Balling, Rudi
Lenhof, Hans-Peter
Meese, Eckart
Keller, Andreas
Language: English
Title: RNA biology
Volume: 16
Issue: 1
Startpage: 93
Endpage: 103
Publisher/Platform: Taylor & Francis
Year of Publication: 2019
Publikation type: Journal Article
Abstract: The validation of microRNAs (miRNAs) identified by next generation sequencing involves amplification-free and hybridization-based detection of transcripts as criteria for confirming valid miRNAs. Since respective validation is frequently not performed, miRNA repositories likely still contain a substantial fraction of false positive candidates while true miRNAs are not stored in the repositories yet. Especially if downstream analyses are performed with these candidates (e.g. target or pathway prediction), the results may be misleading. In the present study, we evaluated 558 mature miRNAs from miRBase and 1,709 miRNA candidates from next generation sequencing experiments by amplification-free hybridization and investigated their distributions in patients with various disease conditions. Notably, the most significant miRNAs in diseases are often not contained in the miRBase. However, these candidates are evolutionary highly conserved. From the expression patterns, target gene and pathway analyses and evolutionary conservation analyses, we were able to shed light on the complexity of miRNAs in humans. Our data also highlight that a more thorough validation of miRNAs identified by next generation sequencing is required. The results are available in miRCarta ( ).
DOI of the first publication: 10.1080/15476286.2018.1559689
URL of the first publication:
Link to this record: hdl:20.500.11880/28750
ISSN: 1547-6286
Date of registration: 20-Feb-2020
Faculty: MI - Fakultät für Mathematik und Informatik
Department: MI - Informatik
Professorship: MI - Prof. Dr. Hans-Peter Lenhof
Collections:UniBib – Die Universitätsbibliographie

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