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JACUSA: site-specific identification of RNA editing events from replicate sequencing data

Piechotta, Michael ; Wyler, Emanuel ; Ohler, Uwe ; Landthaler, Markus ; Dieterich, Christoph

In: BMC Bioinformatics, 18 (2017), Nr. 7. pp. 1-15. ISSN 1471-2105

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Download (14MB) | Lizenz: Creative Commons LizenzvertragJACUSA: site-specific identification of RNA editing events from replicate sequencing data by Piechotta, Michael ; Wyler, Emanuel ; Ohler, Uwe ; Landthaler, Markus ; Dieterich, Christoph underlies the terms of Creative Commons Attribution 3.0 Germany

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Abstract

Background: RNA editing is a co-transcriptional modification that increases the molecular diversity, alters secondary structure and protein coding sequences by changing the sequence of transcripts. The most common RNA editing modification is the single base substitution (A→I) that is catalyzed by the members of the Adenosine deaminases that act on RNA (ADAR) family. Typically, editing sites are identified as RNA-DNA-differences (RDDs) in a comparison of genome and transcriptome data from next-generation sequencing experiments. However, a method for robust detection of site-specific editing events from replicate RNA-seq data has not been published so far. Even more surprising, condition-specific editing events, which would show up as differences in RNA-RNA comparisons (RRDs) and depend on particular cellular states, are rarely discussed in the literature. Results: We present JACUSA, a versatile one-stop solution to detect single nucleotide variant positions from comparing RNA-DNA and/or RNA-RNA sequencing samples. The performance of JACUSA has been carefully evaluated and compared to other variant callers in an in silico benchmark. JACUSA outperforms other algorithms in terms of the F measure, which combines precision and recall, in all benchmark scenarios. This performance margin is highest for the RNA-RNA comparison scenario. We further validated JACUSA’s performance by testing its ability to detect A→I events using sequencing data from a human cell culture experiment and publicly available RNA-seq data from Drosophila melanogaster heads. To this end, we performed whole genome and RNA sequencing of HEK-293 cells on samples with lowered activity of candidate RNA editing enzymes. JACUSA has a higher recall and comparable precision for detecting true editing sites in RDD comparisons of HEK-293 data. Intriguingly, JACUSA captures most A→I events from RRD comparisons of RNA sequencing data derived from Drosophila and HEK-293 data sets. Conclusion: Our software JACUSA detects single nucleotide variants by comparing data from next-generation sequencing experiments (RNA-DNA or RNA-RNA). In practice, JACUSA shows higher recall and comparable precision in detecting A→I sites from RNA-DNA comparisons, while showing higher precision and recall in RNA-RNA comparisons.

Item Type: Article
Journal or Publication Title: BMC Bioinformatics
Volume: 18
Number: 7
Publisher: BioMed Central; Springer
Place of Publication: London; Berlin; Heidelberg
Date Deposited: 04 Jan 2017 13:38
Date: 2017
ISSN: 1471-2105
Page Range: pp. 1-15
Faculties / Institutes: Medizinische Fakultät Heidelberg > Medizinische Universitäts-Klinik und Poliklinik
Subjects: 004 Data processing Computer science
570 Life sciences
610 Medical sciences Medicine
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