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Prioritizing and selecting likely novel miRNAs from NGS data


Backes, C; Meder, B; Hart, M; Ludwig, N; Leidinger, P; Vogel, B; Galata, V; Roth, P; Menegatti, J; Grässer, F; Ruprecht, K; Kahraman, M; Grossmann, T; Haas, J; Meese, E; Keller, A (2016). Prioritizing and selecting likely novel miRNAs from NGS data. Nucleic Acids Research, 44(6):e53.

Abstract

Small non-coding RNAs play a key role in many physiological and pathological processes. Since 2004, miRNA sequences have been catalogued in miRBase, which is currently in its 21st version. We investigated sequence and structural features of miRNAs annotated in the miRBase and compared them between different versions of this reference database. We have identified that the two most recent releases (v20 and v21) are influenced by next-generation sequencing based miRNA predictions and show significant deviation from miRNAs discovered prior to the high-throughput profiling period. From the analysis of miRBase, we derived a set of key characteristics to predict new miRNAs and applied the implemented algorithm to evaluate novel blood-borne miRNA candidates. We carried out 705 individual whole miRNA sequencings of blood cells and collected a total of 9.7 billion reads. Using miRDeep2 we initially predicted 1452 potentially novel miRNAs. After excluding false positives, 518 candidates remained. These novel candidates were ranked according to their distance to the features in the early miRBase versions allowing for an easier selection of a subset of putative miRNAs for validation. Selected candidates were successfully validated by qRT-PCR and northern blotting. In addition, we implemented a web-server for ranking potential miRNA candidates, which is available at:www.ccb.uni-saarland.de/novomirank.

Abstract

Small non-coding RNAs play a key role in many physiological and pathological processes. Since 2004, miRNA sequences have been catalogued in miRBase, which is currently in its 21st version. We investigated sequence and structural features of miRNAs annotated in the miRBase and compared them between different versions of this reference database. We have identified that the two most recent releases (v20 and v21) are influenced by next-generation sequencing based miRNA predictions and show significant deviation from miRNAs discovered prior to the high-throughput profiling period. From the analysis of miRBase, we derived a set of key characteristics to predict new miRNAs and applied the implemented algorithm to evaluate novel blood-borne miRNA candidates. We carried out 705 individual whole miRNA sequencings of blood cells and collected a total of 9.7 billion reads. Using miRDeep2 we initially predicted 1452 potentially novel miRNAs. After excluding false positives, 518 candidates remained. These novel candidates were ranked according to their distance to the features in the early miRBase versions allowing for an easier selection of a subset of putative miRNAs for validation. Selected candidates were successfully validated by qRT-PCR and northern blotting. In addition, we implemented a web-server for ranking potential miRNA candidates, which is available at:www.ccb.uni-saarland.de/novomirank.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Neurology
Dewey Decimal Classification:610 Medicine & health
Date:7 April 2016
Deposited On:18 Nov 2016 09:34
Last Modified:18 Aug 2017 10:40
Publisher:Oxford University Press
ISSN:0305-1048
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/nar/gkv1335
PubMed ID:26635395

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