Background: Massive parallel sequencing of transcriptomes revealed the presence of miRNA variants named isomiRs. The sequence variations identified within isomiR molecules can affect their targeting activity, with consequences in gene expression and potential impact in multi-factorial diseases. miRNAs are considered good biomarkers, making their adoption for disease characterization highly desirable. Several methodologies and tools were devised to identify and quantify miRNAs from sequencing data. However, all these tools are built on-top of general-purpose alignment algorithms, providing poorly accurate results and no information concerning isomiRs and conserved miRNA-mRNA interaction sites. Method: To overcome these limitations we developed the isomiR-SEA algorithm. By implementing a miRNA-specific alignment procedure, isomiR-SEA analysis accounts for accurate miRNA/isomiR expression levels and for a precise evaluation of the conserved interaction sites. As first, isomiR-SEA identifies miRNA seeds within the tags. If the seed is found, the alignment is extended and the positions of the encountered mismatches recorded. Then, the collected info is evaluated to distinguish among miRNAs and isomiRs and to assess the conservation of the interaction sites. Results & Conclusion: isomiR-SEA performance was assessed on 7 public RNA-Seq datasets. 40% of reads attributed to miRNAs (189M) comes from mature miRNAs, 50% derives instead from 3’ isomiRs, and the remaining reads account for 5’/SNP isomiRs or combinations between them. Furthermore, about 2% of reads lost some interaction sites. This proves the importance of a miRNA-specific alignment algorithm to correctly evaluate miRNA targeting activity. Expression levels of isomiRs detected in the two experiments were aggregated and classified with two deepness. In experiment 1, isoforms with indel (in one or both ends) are grouped together. Whereas, in experiment 2 we make a distinction between reads aligned on the mature miRNA with insertion (+) or deletion (-) on 5' or 3' ends. This shows the capability of isomiR-SEA to generate enriched results that can be analysed in down-stream analysis customized for the investigation purpose.
isomiR-SEA: miRNA and isomiR expression level detection in seven RNA-Seq datasets / Urgese, Gianvito; Paciello, Giulia; Macii, Enrico; Acquaviva, Andrea; Ficarra, Elisa. - (2017). ((Intervento presentato al convegno Joint 25th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and 16th European Conference on Computational Biology (ECCB) 2017 tenutosi a Prague nel 21-25 July 2017.
|Data di pubblicazione:||2017|
|Titolo:||isomiR-SEA: miRNA and isomiR expression level detection in seven RNA-Seq datasets|
|Autore/i:||Urgese, Gianvito; Paciello, Giulia; Macii, Enrico; Acquaviva, Andrea; Ficarra, Elisa|
|Nome del convegno:||Joint 25th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and 16th European Conference on Computational Biology (ECCB) 2017|
|Data del convegno:||21-25 July 2017|
|Luogo del convegno:||Prague|
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